Abstract

In the past decade we have observed a rapid development of ultrahigh-speed optical coherence tomography (OCT) instruments, which currently enable performing cross-sectional in vivo imaging of biological samples with speeds of more than 100,000 A-scans/s. This progress in OCT technology has been achieved by the development of Fourier-domain detection techniques. Introduction of high-speed imaging capabilities lifts the primary limitation of early OCT technology by giving access to in vivo three-dimensional volumetric reconstructions on large scales within reasonable time constraints. As result, novel tools can be created that add new perspective for existing OCT applications and open new fields of research in biomedical imaging. Especially promising is the capability of performing functional imaging, which shows a potential to enable the differentiation of tissue pathologies via metabolic properties or functional responses. In this contribution the fundamental limitations and advantages of time-domain and Fourier-domain interferometric detection methods are discussed. Additionally the progress of high-speed OCT instruments and their impact on imaging applications is reviewed. Finally new perspectives on functional imaging with the use of state-of-the-art high-speed OCT technology are demonstrated.

© 2010 Optical Society of America

1. Introduction

The rapid technological growth that took place in the past century led to the emergence of new fields of research and technology having an unprecedented impact on basic biomedical research and clinical medicine. Scientific results obtained nowadays are used in the development of medical imaging commonly applied in clinical practice. Where possible, an attempt is made to eliminate and substitute invasive and contact methods in favor of others that provide similar results without having a negative impact on the examined object. A significant role among modern medical imaging techniques is played by optical methods, including fluorescent imaging, endoscopy, scanning laser microscopy, multifocal microscopy, and optical tomography.

The first attempt towards noninvasive optical imaging at the cellular level in vivo was the use of a confocal microscope. This method enables one imaging of a thin tissue layer by eliminating light emerging from other layers, which is a typical problem of conventional microscopy or classic endoscopy [1]. Unfortunately, the isolation of a very thin layer in confocal microscopy is a result of using significantly high-numerical-aperture objectives, which require placing the sample in close proximity to the objective [1]. Therefore, only superficial layers and tissues, such as the corneal epithelium, may undergo imaging.

The optical method that enables one to increase the working distance and improve the axial resolution compared to confocal microscopy [1] is optical coherence tomography (OCT) [2, 3, 4]. In the original version from 1991, time-domain OCT (TdOCT) enabled researchers to obtain cross-sectional images of relatively low quality [2, 5, 6]. This was mainly due to physical limitations influencing the measurement time, sensitivity, and resolution of the TdOCT method. For the same reasons, it has hardly been possible to perform an in vivo imaging of the entire three-dimensional structure of the examined object by TdOCT. Subsequent scientific studies have shown that the change from time-domain to Fourier-domain detection enables one to increase the acquisition rate over 100 times. An additional advantage of this method is that it is possible to separate dependence on axial resolution (defined as the resolving power of the imaging system in the direction parallel to the probing light beam) from the imaging speed [7, 8, 9, 10, 11, 12, 13]. Thanks to these features it became possible to reconstruct a 3D structure with axial resolution in micrometer-scale from in vivo measurements [14, 15].

The motivation for research works conducted in the field of OCT, which constituted the drive of many scientific groups in the past decade, was the idea of improving the clinical applicability of this method by increasing the resolution and speed of registering cross-sectional OCT images. It has been noticed that this may lead to the emergence of new tools that allow for an early diagnosis of pathomorphological changes in ophthalmology, and in other fields of medicine.

2. Physical Fundamentals of OCT in the Time and Fourier Domains

2A. Low Coherence Interferometry

OCT is an optical modality that enables one obtaining cross-sectional or 3D reconstructions of semitransparent tissue by measuring the echo time delay and magnitude of backreflected light. In some sense it can be compared to ultrasound, but in OCT distances between backscattering or backreflecting layers within the object are measured using light instead of sound waves. Application of light potentially can result in obtaining resolution at a cellular level, as in traditional microscopy. On the other hand, because of the high speed of light, a direct measurement of “optical echo” is impossible. Therefore, OCT uses interferometric techniques with ultrashort light pulses or partially coherent light to range distances at the level of single micrometers.

The general scheme of an interferometric OCT setup is presented in Fig. 1. Here, the amplitude of electromagnetic radiation in the Michelson interferometer is divided into two parts by a beam splitter. Let us denote the electromagnetic field of the light beam directed into a reference mirror as E0ref(t). The second light beam, described as E0sampl(t), illuminates the examined object and is backreflected by its structural elements. The light wave returning from the object is a superposition of waves arriving with different delays τ=Δz/c:

Esampl(t)=nEsampl(t+τn).
This wave is superimposed onto the wave that returns from the reference mirror. In such a configuration we have more than two interfering optical fields:
E(t)=Eref(t)+nEsampl(t+τn),
In the experiment one measures the light intensity I(t), i.e., the amount proportional to the squared and averaged electric field:
I=E*(t)E(t).
Thus, the intensity at the output of the interferometer may be expressed as
I(τ)=I0(ar+nan+2mnanamRe{γss(τnm)}+2naranRe{γ(τn)}),
where ar and an are values of attenuation of light in the reference and sample arm of the interferometer, including reflectivity and attenuation of the nth layer of the sample and the reflection coefficient of the reference mirror, I0 is light intensity entering the interferometer, γ(τ) is the complex degree of coherence related to the autocorrelation (coherence) function Γ(τ) by [16]
γ(τ)=Γ(τ)I0refI0sampl=|γ(τ)|exp(-iωτ),
and the autocorrelation function is defined as
Γ(τ)=E*(t)E(t+τ).

2B. Time-Domain OCT

The values τnm in Eq. (4) are delays of waves returning from different layers within the examined object and do not depend on the position of the reference mirror. Thus, while measuring the signal for the constant position of the reference mirror, the detector will register only one value of light intensity. After introducing the variable τr by movement of the reference mirror, the registered signal may be expressed in the following way:

I(τr)=Const+2I0naran|γ(τn)|cos(ωτn).
In reality, the function |γ(τn)| is a normalized coherence function, and its envelope, similarly to the envelope of the coherence function, depends on the spectral shape S(ω) of the used light. According to the Wiener–Khintchine theorem, S(ω) and Γ(τ) are related via a Fourier transformation:
S(ω)=12π-+Γ(τ)exp{iω(τ)}dτ.
Use of partially coherent light will cause the interferometric oscillatory signal to be visible only if the light delays coming from the reference mirror and the reflecting surface in the object are equal to each other within the coherence time tc. The information on the structure of the object along the probing beam is obtained by registering an optical signal during the shifting of the mirror, therefore the method is also called TdOCT. Delays τ, for which an oscillatory signal is observed, allow for determining a localization of reflecting interfaces separating media characterized by different refractive indices, and thus for determining the depth-dependent distribution of the refractive index changes. By analogy to ultrasound, information about the backscattered light intensity and the reflecting points of the registered light is called an optical A-scan. The cross- sectional image may be constructed in a simple way by collecting many A-scans measured for adjacent positions of the sampling beam. The final graphic representation of the cross-sectional image is obtained by displaying the value of light back reflected intensity in the depth function Z and in one of the transverse directions, X or Y. The intensity value is coded by grayscale or false color on a logarithmic scale to obtain the optimal image contrast. The general operational rule of TdOCT is presented in Fig. 1. The above-described method of measuring layer thickness was used for the first time in 1990 by Fercher [17]. Two-dimensional cross-sectional imaging of biological objects was demonstrated in 1991 and was referred to as OCT [2].

2C. Fourier-Domain OCT

An alternative solution to time-domain detection is Fourier-domain optical coherence tomography (FdOCT) [18, 19, 20, 21, 22]. Here, information on the location of reflective points along the sampling beam is coded in the frequency of oscillatory signal modulating an original spectrum of the light source.

Electromagnetic field used in OCT consists of many optical frequency components, meaning that the light spectrum S(ω) has a broad spectral bandwidth amounting in practice to hundreds of nanometers. For the sake of clarity we can assume that the spectral shape S(ω) is not modified in either the reference or sample beams. Then using the Fourier transformation Eq. (4) can be rewritten in the Fourier domain to the following form:

Stotal(ω)=S(ω)[(ar+nan+2mnanamcos(τnmω)+2narancos(τnω)],
where coefficients an characterize the relative attenuation of backreflected light coming from measured sample. The optical frequency-dependent distribution of light intensity described in Eq. (9) and registered in the interferometric setup is called a spectral fringe pattern. For practical reasons, the measurement of this signal is more often performed as a function of optical wavelengths instead of optical frequencies. This causes a nonlinear distribution of phase of registered oscillatory signal, and it is usually corrected in signal postprocessing. In order to reconstruct the axial structure of the measured object, it is necessary to apply an inverse Fourier transformation:
I˜(τ)=IFTωτ{Stotal(ω)},I^(τ)=(ar+nan)Γ(τ)+mnanam(Γ(τ)δ(τ±τnm))+naran(Γ(τ)δ(τ±τn)).
It may be noted that here, in contrast to Eq. (7), all components, including those describing mutual interference between light beams coming back from the object, depend on the same variable τ. Moreover, there are signal components that originate from mutual interference between light waves backreflected within an object. In practice this matter is even more complicated because in actual systems, apart from information coming from the object, there also exist many reflections within the measurement instrument that also contribute to the total signal collected and are analyzed by the OCT device. These all components are referred to as coherence noise. The easiest way to eliminate the coherent noise not correlated with the object is to subtract the signal registered when the object is not present in the sampling arm. It is more difficult to get rid of coher ence noise connected to the measured sample.

In the case of thin objects, which are at least twice as thin as the total measurement range, there is the possibility of separating the coherence noise components from the object’s structure reconstruction via a proper selection of the optical path difference between the reference mirror and the first surface of the examined object [20]. Another way would be to select optimal parameters of the measurement system in such a way that the squared amplitudes of the coherence noise components would be smaller than the variance of the regular white noise detected by the OCT setup [23]. In addition, as STotal(ω) is a real-valued function; it follows that I^(τ) is a Hermitian function (its complex conjugate is equal to the original function) [24]. Therefore, when recreating the structure of the examined object from one spectral fringe pattern we shall obtain two symmetrical images (Fig. 2). When the position of the reference mirror corresponds to the surface within the examined object, the real reconstruction of this object will be situated both in the positive as well as in the negative τ. In this case, symmetric images will be superimposed on each other, which prevents a reliable analysis of the observed structure. The influence of all undesired effects in FdOCT is presented in Fig. 2.

There are two main ways of designing and constructing FdOCT instruments. The first one is called spectral (spectral-domain) optical coherence tomography (SOCT), in which the detection of the interferometric signal is made by a spectrometer equipped with a high-speed line scan detector, e.g., a CCD or complementary metal oxide semicondcutor (CMOS) [11, 12, 20, 25, 26]. The second one is called swept source OCT, which uses high-speed tunable lasers. This method is also called optical Fourier- domain imaging (OFDI) [22, 25, 27, 28, 29, 30, 31, 32, 33].

Figure 3 shows simplified diagrams of FdOCT instruments. In both methods the information about the structure of the examined objects is obtained by applying numerical Fourier transformation (in practice fast Fourier transform) to the spectral fringe signal. Compared to TdOCT, FdOCT instruments are mechanically more stable due to stationary reference mirror, and both techniques enable an increase of measuring speed, preserving comparable sensitivity by a factor of over 100.

2D. Optical Frequency Windows and Resolution in OCT

As with all other optical methods, OCT imaging makes sense only when light manages to get through to the examined layers and outside to the detection system. Therefore, it is necessary for the sampling beam to be weakly absorbed and scattered before it gets to the target and then to the detector. In tissue measurements using a visible range light (400600nm) the dominant absorption is due to erythrocytes and melanin in the skin, while in the near-infrared region (6001500nm) water absorption becomes more important [1, 34]. Taking into account the influence of these three components, in the case of biological objects it seems optimal to use light sources within the wave range of 700nm to 1300nm [34]. An optimal choice of the spectral range depends on the application in which we want to use OCT imaging. In order to achieve maximum axial resolution (14μm), e.g., in optical coherence microscopy or retinal imaging, an optical frequency spectral window centered at 800mm is typically used. To get information from deeper layers with relatively high axial resolution of 615μm, e.g., in endoscopic OCT [35, 36, 37], intravascular imaging [37, 38] or imaging of the anterior segment of the human eye [39, 40, 41], broadband light centered at 1300nm is applied. Another spectral range used in OCT imaging is broadband electromagnetic radiation with the central wavelength of 1000nm [42, 43, 44, 45]. Compared to 800nm the tissue penetration is somewhat higher, at the cost of axial resolution (410μm). Other limitations for using specific optical frequency windows are caused by technological limitations of detectors and accessibility of light sources. The use of swept laser sources is optimal for imaging in the 1300nm and 1000nm wavelength range, where low-cost and low-read-noise cameras are not available. On the other hand, to our knowledge there are still no developed robust high-speed swept sources at 800nm with a large spectral bandwidth.

The axial resolution in both the TdOCT and FdOCT methods is determined by the coherence time or the coherence length lc of applied light. In the case of the Gaussian shape of the coherence function and also bearing in mind that the light travels back and forth in the interferometer, the axial resolution is expressed by the formula

Δz=lc2=12tcc=2ln2πnλ02ΔλFWHM,
where λ0 describes the central wavelength, ΔλFWHM is the full width at half-maximum of the spectral profile, and n is the refractive index of the sample. Similarly to the confocal microscopy the transverse resolution in OCT is determined by the size of the focused spot of scanning beam [3].

2E. Time-Domain OCT versus Fourier-Domain OCT

The main advantage of time-domain detection is an automatic removal of coherence noise. Also the problem of symmetric images is automatically eliminated in TdOCT, because scanning takes place exactly in the function τ. Thus, there is no possibility of a simultaneous observation of two values of the optical path difference at the same time. Another important advantage of methods with time domain is the possibility of reversing the scanning sequence and registering en-face images as first in a parallel way (full-field OCT) [46, 47, 48], and with transverse scanning (en-face OCT) [49, 50, 51]. Such measurement configurations provide flexibility in choosing the carrier frequency of the interferometric signal used in experiments, thanks to which the signal-to-noise ratio (SNR) may be optimized [52]. Full-field OCT is especially attractive in biological applications as a substitute for microscopic imaging [53, 54], while en-face OCT may be applied for example in imaging of the fundus of the eye, allowing one to obtain full correspondence to the use of scanning laser ophthalmoscopy [55].

There is, however, a strong limitation of TdOCT related to the efficiency of electrical filtering of the interference fringe signal. In order to understand this limitation it is necessary to analyze carefully the SNR of OCT detection. One of the main noise sources in optical OCT is shot noise, which is present in OCT signals along with the read noise and light intensity fluctuations originating from the light source itself—so-called relative intensity noise (RIN). An optimal situation arises when the level of shot-noise-limited detection is achieved. Shot noise has a Poisson distribution and it is related to the discrete nature of the photocurrent generated by the semiconductor junction in the presence of photons hitting the photodetector. When the DC components of analyzed signals are filtered out the variance of the photocurrent is equal to the root mean square (rms) value of the photocurrent (irms)2, which is expressed by the following formula [56]:

σs2=(irms)2=2e-iavΔf,
where e is the electron charge, iav is the average photocurrent registered by the detector, and Δf is the electronic detection bandwidth registered by the detector.

Table 1 compares the signal fluctuation connected with shot noise, as well as squared values of signal amplitudes for time- and Fourier-domain detection calculated according to analysis presented by Leitgeb et al. [57]. For the purpose of comparing both methods it has been assumed that the measurement of a single optical A-scan is performed at the same time T and that an identical light source was used at the same optical power P0 with a Gaussian spectral shape. The sensitivity of the applied imaging method constitutes a particularly important parameter in biomedical imaging [25, 57, 58, 59, 60]. In optical OCT tomography this parameter specifies the weakest detectable signal. It is expressed by the relation

Sens=10log(1Rmin),
where Rmin represents the sample reflectivity coefficient at which the amplitude of the interference signal is equal to variance of noise, SNR=1. When setting the sensitivity of the method it is assumed that RSRr.

Another parameter that characterizes optical OCT tomography systems is the dynamic range [25]. The dynamic range is specified by the SNR obtained for the maximum value of the interference signal. This number suggests how big the difference between two simultaneously registered recognized SOCT signals may be. The dynamic range is set with the assumption that we are dealing with two equal intensities of light coming from both interferometric arms, RS=Rr=1/4Rmax, where Rmax depicts the value of the sample reflectivity coefficient with which the detector is saturated. Table 1 shows the values of sensitivity and dynamic range of the TdOCT method along with FdOCT in case of shot-noise-limited detection.

A comparison of formulas listed in Table 1 leads to the conclusion that the SNR in the TdOCT and FdOCT is expressed by almost similar dependency in the physical sense. What differentiates TdOCT from SOCT and OFDI are factors determining the selection of time constants (electrical bandwidth) responsible for the signal integration through a detection process. In TdOCT, the electronic detection bandwidth of the oscillatory signal that provides structural information is strictly connected with the scanning speed, as well as with the axial resolution [3, 4]. For SOCT, determination of modulation frequencies of the measured spectrum is essential for structure reconstruction. In this case SNR depends directly on camera integration time, and the latter (for purpose of comparison) may be expressed in terms of effective bandwidth Δf=1/(2T). In OFDI, as in TdOCT, sampling is done as a function of time, but as a result of the Fourier transformation the signal including noise is integrated over the sweep time of the tunable laser. Hence, in the case of the shot-noise-limited detection, the electronic detection bandwidth is getting narrower, reaching the level of an effective electronic bandwidth determined by the sweep rate of the tunable laser.

In order to understand the advantage of FdOCT over TdOCT, we shall analyze in detail the conditions of an optimal selection of electronic detection bandwidth in the TdOCT method. Here, the electronic bandwidth is determined by the measurement time determined by the speed of the optical delay line [3]:

Δf2Zmaxλ02TΔλ,
where T is the measurement time of a single optical A-scan, λ0 is the central wavelength, ΔλFWHM is the FWHM of the spectral bandwidth, and Zmax is the optical length corresponding to the maximum axial imaging range (optical length of a single A-scan). Finally, the SNR in TdOCT is
SNRTdOCT=λ02ZmaxΔλFWHMρP0TeγrγsRrRs(Rr+Rs).
Because of the presence of the coefficient ΔλFWHM in Eq. (15), the electronic bandwidth, as well as the SNR in TdOCT depend on the axial resolution, which in turn depends on the optical bandwidth of the light, Eq. (11). By combining Eqs. (11, 15) and the SNR value from Table 1, one can express the SNR values in the Fourier- and time-domain methods by the following relation:
SNRFdOCT=2ln2π·ZmaxΔzSNRTdOCT.
Using OCT for tissue imaging, the ratio of the axial imaging range Zmax to the axial resolution Δz is much higher than 1, in practice reaching values of 103, which in accordance with Eq. (16) gives an improvement of the SNR to approximately 25dB. From the same equation it may be also concluded that the increase of axial resolution is more favorable for the FdOCT method. It should be stressed that the sensitivity advantage of FdOCT over TdOCT occurs only for a certain well-defined setup, where the ratio of Zmax to Δz is a much larger than 1.

Besides shot noise, read noise and RIN may have an impact on imaging quality in OCT tomography [56, 61]. The main components of read noise are thermal: Johnson noise, dark noise, and 1/f noise. Among these, the most prominent is Johnson noise, with the variance σJ expressed with the following formula [61]:

σJ2=4kTΔfR,
where Δf is the electronic detection bandwidth, k is the Boltzmann constant, T is the absolute temperature, and Ris the resistance of the detection electronics. The most important is the temperature dependence: Johnson noise usually obtains high values for room temperature. The RIN noise means any signal connected to light fluctuation, for which the variance of the registered photocurrent is proportional to the square value of the average photocurrent:
σRIN2=Be-i¯2,
where B denotes the scaling factor dependent on the mechanism responsible for the light fluctuations. The causes for such fluctuation may be numerous, for example intensity changes connected with amplified spontaneous emission, fluctuations caused by light generation in the active medium (crystals or semiconductors) of the laser cavity, or random phase fluctuations in the interferometer setup.

Assuming that the influence of read and RIN noise is essential, they will add to the shot noise and together determine sensitivity value:

SNR=|AC|2σs2+σj2+σRIN2,
where |AC|2 is the squared value of the amplitude of the oscillatory signal, σs2 is the variance of photocurrent related to the shot noise, σj2 is the variance of photocurrent related to the read noise, and σ2RIN is the variance of photocurrent related to the RIN. In the experimental configuration, where the influence of thermal noise and fluctuation may be considered negligible, the increase of optical power from the reference arm by a factor of n causes the increase of the signal value and shot noise by n. Thus, this does not influence the SNR value. In such a situation we speak about shot-noise-limited detection. There are, however, two limitations. First, the optical power from the reference arm may be increased only to the detector saturation level. Second, the increase of optical power causes the RIN noise to dominate, because of the square dependency on intensity.

In practice, the optimal SNR is established for a situation in which the shot noise begins to dominate. Figure 4 shows two exemplary panels of the sensitivity plotted as a function of light intensity from the reference arm (expressed as the reflectivity of the reference arm) for an SOCT system with a CMOS camera and for a swept source OCT instrument without dual-balanced detection. In both cases the experimental sensitivity increases monotonically with the reflectivity of the reference mirror due to the domination of the read noise component for low values of the reference arm intensity. The top panel shows that SOCT system working with a speed of 250,000A scans/s is able to achieve shot-noise-limited detection. In the case of swept source the effective sweep rate corresponds to 12μs of sweep time. In this setup the read noise and RIN noise are so big that the RIN noise starts to dominate over thermal noise before achieving shot-noise-limited detection. In this particular case the effective sensitivity value is approximately 10dB smaller than expected for the shot-noise-limited detection. In such a situation, the modification of the detection system becomes necessary through the introduction of dual-balanced detection. This configuration uses two light receivers that register a pair of interferometric fringes with a π phase shift between them. Next, the electric signals are subtracted on a differential amplifier. As a result, all light intensity fluctuations whose source is located before the interferometer system (i.e., mainly coming from the source of light) are canceled out and shot-noise-limited detection can be achieved. The example demonstrated in Fig. 4 shows the main difference between the detection performed by low-read-noise line scan detectors such as CCD or CMOS and photodiodes. In CCD/CMOS detectors the read noise and the saturation level are lower than that in photodiodes, therefore the shot-noise limit can be achieved for smaller light intensity illuminating the detector, preventing the OCT system from the negative influence of RIN noise. As shown in Fig. 4, even for exposure times as short as 4μs, SOCT is able to operate in the shot-noise-limited detection regime. In turn, the swept source OCT can operate with a larger dynamic range, but it is necessary to use a dual-balanced detection scheme to achieve shot-noise-limited detection.

3. Development of Rapid Scanning OCT Instruments

Because of recent technological advances in high-speed CCD cameras, CMOS detectors, and high-speed tunable lasers (swept sources), we are currently thrown in the center of a rapid development of ultrahigh-speed OCT imaging instruments based on Fourier-domain detection. This is confirmed by statistics showing that, during the 18-year history of the OCT method’s development, approximately 50% of all peer-reviewed articles on OCT emerged in the past 3 years (based on ISI Web of Science).

Figure 5 shows a chart of the maximum speed performance of OCT measurement devices published since the emergence of OCT in 1991. The chart clearly shows the dramatic progress in performance of high-speed OCT instruments during the past 5 years, which opens new fields of applications and perspectives for further development of OCT imaging.

3A. Time-Domain OCT

The first system published by Huang et al. at the Massachusetts Institute of Technology demonstrated a laboratory device that enabled imaging with a speed of 2 A-scans/s [2]. The device used a stepping motor with an attached mirror as an optical delay line. Two years later Swanson et al. from the same group demonstrated the possibility of increasing axial scanning to 156mm/s through the use of a galvanometer-based translating retroreflector system [5]. For 1 mm of imaging depth this instrument enabled performing measurements with a repetition rate of 130Hz. Other optical delay lines implemented in OCT using a rotating cube [62] had achieved up to 400 scans/s, but they suffered from a low duty cycle and strong nonlinearities of delay in time. Later, delay lines based on a high-speed resonant scanning mirror were introduced [4], which achieved 3mm scan lengths at 1200Hz. The next modification of the axial scanning system was the use of mechanical stress imposed on the fiber structures to induce the difference of optical paths within a few millimeters with rates of a couple hundred hertz [63]. These techniques, however, suffer from dynamic and static birefringence effects, are unstable in terms of temperature, and may exhibit significant optical losses, especially for an 800nm wavelength range.

However, the real breakthrough in performing quick measurements using the TdOCT method was the introduction of a grating-based phase-control rapid scanning optical delay (RSOD) line. The method was first developed for femtosecond pulse measurement [64, 65]. The first report on the possibility of using a grating-based phased-control RSOD line in TdOCT was published in 1997 by Tearney et al. from MIT [66]. Such an optical delay line may be implemented by the use of a spatially dependent linear phase ramp in the pulse shaping setup. The Fourier transformation of a linear phase ramp introduced to the interferometric signal in the frequency domain results in a delay in the time domain. These ODLs achieve high-speed, high-repetition linear scanning, while simultaneously permitting an independent control of the phase and group delay. Rollins et al. demonstrated examples of biomedical imaging using RSOD line with a scanning speed of 4000 A-scans/s [67].

3B. Spectral OCT (Spectral-Domain OCT)

Another major step in the improvement of OCT imaging speed, which led to obtaining a value of 15,000 A-scans/s, was shown in 2003 by Wojtkowski et al. [7]. They demonstrated a system with Fourier-domain detection, using a custom-made spectrometer with a CCD camera. Because high-speed line scan CCD cameras have just been introduced to the market, the first experiments showing the possibilities of human retinal imaging in vivo with an exposure time of 64μs were performed on a camera with a matrix CCD detector working in a “fast kinetics” mode. In this mode, a 2D CCD camera was used simultaneously as a linear detector and a storage media. Only the first row of the CCD matrix was illuminated, whereas the unexposed part of the CCD chip was masked and used for storing consecutive fringe patterns. The readout of the whole frame started after all rows of the CCD matrix had been filled with data. This procedure enables the acquisition of data with exposition times as small as 16μs per line. These studies showed for what is believed to be the first time the possibility of retinal imaging in vivo via the Fourier method with such short exposure times. At the same time, high-speed line scan CCD cameras started to appear on the market, which used data transfer protocols enabling work with a duty cycle of more than 90%. These detectors were used for constructing high-speed spectrometers in SOCT for both 800nm and 1300nm spectral ranges. New systems using CCD cameras (AViiVA-Atmel/E2V, Goodrich, Basler) made it possible to obtain scanning speeds of 18,000 A-scans/s in 2003 [11], 30,000 A-scans/s in 2004 [10], and 50,000 A-scans/s in 2007 [68, 69]. However, the real breakthrough in imaging speed with the use of SOCT was the application of a high-speed scan camera with a CMOS detector, introduced by Basler (Sprint) and demonstrated in 2008 by Potsaid et al. from MIT [12]. The properties of CMOS cameras make them well suited to be used in OCT imaging because one has the possibility of a flexible choice of active pixels influencing both examination time and the number of voxels, which is not possible in SOCT systems based on CCD cameras. The decreased number of pixels per A-scan can be set for high-speed data acquisition. Potsaid et al. demonstrated SOCT imaging applying CMOS detector with speeds up to 310,000 A-scans/s using only 576 pixels of a CMOS detector. However, it is important to note that in the case of SOCT a decrease of the number of pixels will cause a decrease of either the imaging range or the axial resolution. In experiments demonstrated by the group at MIT a maximum speed of more than 300,000 A-scans/s has been achieved for 1.5mm axial range and 9μm axial resolution. To give a fair comparison to other ophthalmic high-resolution SOCT systems keeping the range more than 1mm and resolution of about 2μm at the same level, the CMOS-based SOCT system can run up to approximately 120,000 A-scans/s [12, 26, 70].

3C. Swept Source OCT (OFDI)

The first three publications indicating future potential of swept lasers in OCT imaging had been already published in 1997 [22, 27, 71]. However, in the first two of them scanning speeds were very small: 0.33 nm/s by Lexer et al. [27] and 10Hz by Chinn et al. [22]. The third publication demonstrated the very interesting idea of using a continuous wave (CW) chromium-doped forsterite laser that enabled rapid wavelength tuning over a broad bandwidth [71]. Spectral filtering for wavelength tuning was obtained by using a sequence of four dispersive, Brewster-cut prisms inserted into one of the collimated arms of the laser. Angular deflection of a ray passing through the prism sequence was strongly wavelength dependent, and only a narrow spectral range was returned after reflection from the resonator end mirror. An angular deflection of an end mirror mounted on a galvoscanner enabled rapid wavelength scanning. Research on new swept sources based on diodes generating amplified spontaneous emission (ASE) assembled as semiconductor optical amplifiers has accelerated dynamically since 2003, simultaneous with the development of the SOCT technique. The promising capabilities of such frequency swept light sources for OCT imaging have generated intense interest in their development. However, the main bottleneck became filtering of the broadband ASE spectrum to initiate laser action for consecutive optical frequencies. Three major concepts to achieve high-speed tuning depending on the method used for wavelength selection inside a short laser cavity of the wavelength swept source were proposed. The first one is based on a fast-rotating polygonal mirror introduced by Yun et al. [[28] initially, enabled for OCT imaging with 15kHz sweep rate and developing up to 115kHz [72, 73]] and at present available commercially (Santec) at 50kHz scanning rate with almost 100% duty cycle. The second one is based on a diffraction grating coupled with a mechanically resonant galvo-scanner. This kind of swept laser was developed in 2005 in a collaborative project between MIT and Thorlabs [32]. At present these light sources are commercially available (Thorlabs), and their application to OCT enables imaging with speeds up to 50,000 A-scans/s [74, 75]. The third way of rapid tuning is using fiber Fabry–Perot tunable filters [33, 76, 77]. This method can be either used in a fiber ring cavity lasers or short cavity open space setups. The first idea was introduced to the market by Micron Optics, and at present it is possible to run OCT experiments using these sources with 40kHz. A feature that makes swept laser technology using fiber Fabry–Perot attractive is its all- fiber-optics platform. Such a combination gives high performance, reliability, low cost, and design flexibility, which allows technology translation to address different spectral regions and custom sweep ranges, coherence lengths, and power levels. One of the crucial parameters in the design of high-speed swept source lasers is the length of the cavity. To ensure that there is enough time to start laser action within the cavity (buildup time) its length must be matched with the sweep rate. This limitation was overcome by significant shortening of the cavity and using resonant microelectromechanical Fabry–Perot filter and a novel optical packaging platform in swept source lasers manufactured by Axsun Technologies. Currently available, Axsun systems enable OCT imaging with speeds up to 100kHz for both 1300nm and 1060nm spectral ranges. For very high tuning speeds and to overcome limitations given by the buildup time of lasing in the cavity, the technique of Fourier-domain mode locking (FDML) has been introduced by Huber et al. in 2005 [78]. In FDML sources, a narrowband optical filter is swept in time equal to the optical round-trip time of the laser cavity. To obtain operation at more than 100kHz the laser cavity length is increased to several kilometers by an additional fiber delay line. In contrast to short cavity lasers, lasing in FDML does not have to build up repetitively. Quasi-stationary operation is achieved in this configuration by forcing each optical frequency component to circulate in the cavity in such way that it is transmitted through the filter at every pass. Compared to conventional wavelength swept lasers, FDML lasers exhibit improved noise performance, coherence length, output power, and higher maximum sweep repetition rate [31, 78, 79, 80, 81, 82]. Currently it has been demonstrated that high repetition rates up to 400kHz can be obtained with FDML swept sources [83]. The weak point of this configuration is strong dependence on the cavity dispersion, which makes it hardly applicable to wavelengths shorter than 1000nm with current optical fiber technologies.

3D. Alternative OCT Techniques

It is important to note that besides standard realizations of the TdOCT and FdOCT methods there exists a broad spectrum of alternative techniques, which are also practical manifestations of the Fourier detection idea. The previous paragraph presented only those methods that are comparable in a direct way. Techniques not mentioned include en-face [84], parallel Fourier-domain OCT [85], full field, and linear OCT [46, 86, 87], which also have a significant impact on the technological development of OCT and its applications.

In this contribution other two alternative methods have to be mentioned simply because they have achieved the highest reported OCT measurement speeds to date. Both are derivatives of the FdOCT, and both of them are still impractical because of technological limitations. However, in the future they may become the most popular implementation of Fourier-domain detection. In the first one, related closely to the swept source OCT technique, the tunable laser was substituted with a fiber-based highly dispersed optical line that enabled femtosecond pulse stretching to 70ns and a registration of time-dependent optical frequency variables along the stretched pulse. The imaging speed, which may be obtained by using the proposed solution, is 5000kA-scans/s [88]. This technique of rapid sweeping was also used in spectroscopy by Sanders et al. [89]. The second interesting solution is a method based on SOCT that used parallel optical signal detection obtained with the aid of a fiber demultiplexer with 256 channels [90]. The great advantage of such a system is the possibility of separating optical frequencies in equal frequency intervals and obtaining high spectral efficiency and resolution. The latter approach enables one to achieve a reduced sensitivity drop-off of 10dB for 12mm. Choi et al. demonstrated the functioning of this system with a dizzying registration speed of 60,000,000 A-scans/s. Authors of these experiments supervised by Ohbayashi referred to their solution as an optical demultiplexer-OCT [90]. Unfortunately, the disadvantage of the presented setup is the need to apply multiple discrete dual-balanced detectors, which necessitate the use of 512 amplified photodiodes. However, these limitations are not fundamental and can in future be overcome by further development of photonic technologies.

4. Applications of High-Speed OCT Imaging

4A. Ophthalmology

The biggest limitation of optical methods used in biomedical imaging is the relatively small light penetration into a tissue at the order of magnitude of single millimeters. In OCT, the multiple scattering of light reduces the quality of reconstructed images. Therefore, the usable range of this method is limited to weakly scattering biological samples. These include all internal organs containing only small amounts of melanin and hemoglobin. From this point of view, elements that are best suited for imaging with the use of visible or near-infrared radiation, include the human eye, especially such structures as conjunctiva, cornea with a tear film, crystalline lens, optic nerve head, and retina. The majority of the mentioned anatomic structures are weakly scattering for visible light.

During clinical trials conducted by many research groups between 1995 and 2005, the usefulness of cross-sectional images, mainly of eye tissues obtained with the use of TdOCT, has been confirmed in medical diagnosis [4, 6, 39, 91, 92, 93, 94, 95, 96]. In the majority of cases, apart from some ophthalmological cases including glaucoma, it could be applied to detect very advanced pathological changes that could also be diagnosed with the use of other instruments. In addition, due to the low speed of registering TdOCT images, obtaining a 3D structure was impossible, which in turn hindered a thorough analysis of the received images for clinical diagnosis. Attempts have been made to minimize the imperfections of the measurement method through the use of sophisticated and highly specialized scan patterns.

The first retinal images obtained by the Fourier-domain detection were shown in 2002 with an effective speed of 1000 A-scans/s [20] and in the next year with a registration speed of 15,000 A-scans/s [7]. In that same year group at Nicolaus Copernicus University (NCU) conducted experiments with high-axial-resolution (approximately 3μm) retinal and corneal imaging with registration speed of 8000 A-scans/s, using a supercontinuum light source with photonic fiber pumped by the femtosecond laser [8]. Also three other groups presented experiments demonstrating high-speed ultrahigh-resolution retinal imaging with a 3.5μm axial resolution at 15,000 A-scans/s [13], a 2.5μm axial resolution at 10,000 A-scans/s [97], and a 2.1μm axial resolution at 16,000 A-scans/s [14], using femtosecond lasers and broadlighters.

One of the most important effects of using high-speed OCT retinal imaging with Fourier-domain detection is the substantial improvement in the quality of cross-sectional images. A comparison of in vivo cross-sectional images of the human retina in the macular region obtained by TdOCT versus FdOCT is presented in Fig. 6. The improvement of imaging quality is mainly caused by the shortening of measurement time, which as a consequence also enables one to acquire an increased amount of data during the examination. The second factor determining quality improvement is a substantial increase of axial resolution obtained due to the use of a spectrally broadband light source (femtosecond laser), which is the result of a lack of a fundamental relationship between imaging sensitivity and axial resolution in the case of FdOCT.

In addition, in FdOCT the interference fringe signal is not processed by analog electronics, and all operations enabling object reconstruction are performed on digital data. This allows for a better compensation of unfavorable effects influencing the loss of resolution than in the case of TdOCT. Figure 7 shows a high-resolution (2.5μm in the tissue) cross- sectional retinal image scanned along the pappillomacular axis obtained with the SOCT system using a femtosecond laser and high-speed CMOS camera. Besides the high quality, the rapid registration enables one to avoid undesirable effects coming from the patient’s movement [9, 98].

An early diagnosis of pathological changes of the optic nerve and the central retina has a fundamental impact on their effective treatment. Macular retinal diseases are a large group of diseases that encompass, among others, degenerative changes, e.g., age- related macular degeneration (AMD), retinal and choroid circulation disorders, e.g., retinal vein occlusion or diabetic retinopathy, vitroretinal disorders, e.g., tractions, epiretinal membranes, and macular holes, and retinal detachments such as central serous retinopathy. These diseases are usually connected with considerable changes in tissue morphology that may be observed in OCT cross-sectional images. Figures 8a, 8b, 8c, 9a, 9b, 9c show examples of high-quality and high-resolution OCT images (3.5μm) of retinas with a variety of pathological changes. These images were obtained via a prototype clinical instrument designed and constructed in the Institute of Physics at the NCU, and the measurements were conducted at the ophthalmology clinic at the NCU.

AMD may occur in two forms: nonexudative [Figs. 8a, 8c] and exudative [Fig. 8b]. In case of nonexudative AMD we may deal with smooth elevations of the retinal pigment epithelium (RPE) by very short soft drusen [Fig. 8a] or considerably larger changes caused by large confluent drusen [Fig. 8c. Drusen in OCT images are visible as irregularities of a highly reflecting double line corresponding to RPE and the outer segments of photoreceptors. The outer limiting membrane is elevated as well. This means that entire photoreceptors are shifted anteriorly. In some cases the material responsible for increased reflectivity is also visible inside the drusen (under the RPE).

Depending on the composition of drusen, their size, and the stage of the disease’s development, values of backreflected light intensity from drusen areas may differ considerably. In some cases, as shown in Figs. 8a, 8b, 8c, the basal part of drusen may be recognized, pointing to the location of Bruch’s membrane. In exudative AMD blood vessels grow abnormally (choroidal neovascularization), passing through Bruch’s membrane, and then proliferate under the RPE and/or under the retina, forming a fibrovascular membrane (so-called choroidal neovascular membrane), which is the source of numerous complications. Figure 8b illustrates retinal cross-sectional images in the case of advanced changes connected with exudative AMD. The shape of the foveal pit is deformed, and the entire neurosensory retina is elevated. Also, a highly scattering structure is visible that corresponds to the fibrovascular membrane forming a fibrous scar.

High-resolution OCT is possibly the best method of discovering macular holes and specifying the stage of this disease, facilitating the decision about a possible operation. Cross-sectional images obtained via OCT enable one to precisely distinguish between a full-thickness macular hole and a laminar macular hole. Figure 9a shows an exemplary OCT cross-sectional image of a patient with a full-thickness macular hole.

Another group of diseases that may cause numerous changes in retinal morphology are those in which elevations of the neurosensory retina from the RPE occur—this is the case with, e.g., central serous chorioretinopathy [CSCR, Fig. 9b]. This is one of the few diseases with well-defined morphological changes. This case is, however, interesting from the point of view of OCT imaging, because it can help one to perform exact interpretation of posterior retinal layers visible in cross-sectional OCT images. According to the current medical knowledge, in the course of the disease, serous fluid accumulates close to the RPE, elevating the neurosensory retina in the direction of the vitreous. In the majority of cases, after the fluid is resolved the disease symptoms withdraw, and visual acuity improves to 20/20. This means that the function of photoreceptors and their structure are retained despite the separation of the neurosensory retina from the RPE. The outermost and the brightest layer visible in the cross-sectional image adheres to the neighboring tissue indicating that this layer may correspond to the RPE.

An important area of OCT use may be the diagnostics of diseases connected with a photoreceptor dysfunction. It is vital to discover the disease before clear structural changes of the retina occur, which usually lead to permanent photoreceptor impairment. Figure 9c shows an example of a cross- sectional image registered in the case of a retinal disease occurring with a photoreceptor dysfunction. Retinal layers look normal in the fovea; however, in the periphery of the macula an IS/OS reflectivity decreases gradually until its total disappearance on the image’s edges, where the “sinking” of the sensory retina occurs, indicating a complete atrophy of photoreceptors.

One of the most important advantages of FdOCT is the possibility of measuring OCT data in all three dimensions. This enables one to create virtual volumetric (3D) reconstruction of the structure of the examined object. Information about the 3D structure of the examined object can be retrieved from consecutive cross-sectional images measured for the variable transverse position of the scanning beam. The full volumetric information about the eye’s fundus enables a reconstruction of the cross-sectional image along any arbitrarily chosen plane. However, the practical use of 3D data is far greater than in only the spatial reconstruction of the structure or any surface. Thanks to the combination of imaging with three dimensions and high resolution we may precisely find the position of the place in which the analyzed sectional image is located. This is especially useful in the case of retinal imaging, where direct methods of examining the eye’s fundus, fundus photography and fluorescein angiography, remain the gold standard. These methods register the projection of all retinal layers, choroid, and sclera into the plane perpendicular to the optical axis of the imaging instrument. Diagnostic ophthalmology experience has been gathered for many years on the basis of this information. Thus, the possibility of an accurate registration of cross-sectional images with respect to fundus photography and direct ophthalmoscopic analysis has a significant clinical importance. With 3D OCT data it is possible to create an image of the fundus of the eye analogous to images obtained by the use of scanning laser ophthalmoscopy [8, 9, 99]. The simulation of such an image is possible thanks to the averaging of backreflected intensity along the axis determined by the direction of light propagation [Fig. 10a].

A SOCT fundus image clearly reconstructs the retinal vasculature and, in the case of disease changes, provides information about the location of these changes. Such an image is not identical to a color fundus photo because it has been obtained as a result of illuminating the object with near-infrared light. Additionally, it is distorted with speckle noise. The retinal vasculature may be used for a superposition of OCT data on the fundus photo or on the angiography image. This enables a very precise localization of the line along which the OCT cross-sectional image was measured. Once the 3D data are acquired, it is also possible to generate projections in the way described above, however, this time by using only a certain fragment of the volume. In the case of the retina we may choose data corresponding to a specific tissue layer and create its projection, called retinal reflectivity maps [Fig. 10b] [9, 99, 100, 101, 102].

Three-dimensional retinal imaging enables one also to perform quantitative morphometric analysis of retinal layers. An accurate quantitative data processing of 3D OCT measurements may efficiently support ophthalmological diagnostics if the method is based on an analysis of real physical parameters, such as the thickness of layers, distances between characteristic points, the volume of chosen structures, the thickness of the reconstructed layers, the distance between characteristic points, or the volume of structures of interest. Furthermore, a high repetitiveness and specificity of a given processing method should be guaranteed. 2D contour maps obtained from 3D OCT data have two basic advantages: First, they enable a quick assessment of the condition of retinal structure without the necessity of studying cross-sectional images one after the other. Second, each of the contour maps is created based on another physical value, thanks to which the statistical specificity of a given analysis can be increased. Another purely practical advantage is the possibility of obtaining by one instrument information, which was previously offered by a couple of independent diagnostics devices.

One of the ways of quantitative specification of fundus morphology is the measurement of the full retinal thickness. This kind of analysis can be important in the case of a macular edema, which may be a result of many diseases, such as diabetic retinopathy, epiretinal membrane, retinal vein occlusion, or an effect secondary to cataract surgery. The thickness of retinal layers is determined with the use of segmentation algorithms that enable one to distinguish the anterior and posterior retinal surface and to calculate the difference between them. Results are displayed as a contour map whose colors correspond to adequate thicknesses [9].

Other clinically significant quantitative information that may be obtained as a result of 3D imaging via FdOCT concerns the nerve fiber layer (NFL) thickness. It is especially important in diagnostics and treating glaucoma. Figure 11 shows the result of determining the nerve fiber layer thickness by FdOCT. Compared to a scanning laser polarimetry (GDx Vcc) device, the advantage of the described method is its lack of polarization dependence [9]. As has been shown in Fig. 11, the contour map of the nerve fiber thickness may be precisely correlated with the color fundus photo. Other quantitative parameters characterizing the optical nerve head, which are important in glaucoma diagnostics, are so-called stereometric parameters of the optic disc.

These parameters include the area and volume of the optic disc and the cup. Such an analysis may be performed with the use of Heidelberg retinal tomograph, which in fact is an improved scanning laser ophthalmoscope. However, the weakness of this technique is the necessity of manually setting the contour line coinciding with the rim of the optic disc, defined as the internal edge of Elsching’s scleral ring. Any inaccuracy in determining this contour causes considerable errors in evaluating the condition of the eye, especially in cases of early degenerative changes. The introduction of the Fourier detection to OCT imaging enables for the first time the combination of high-quality topographic information, as in the Heidelberg retinal tomograph device, with high-quality cross- sectional images. Thanks to this there is a possibility of performing a fully automatic procedure of determining stereoscopic parameters [9].

Detailed analysis of OCT signals corresponding to outer retinal layers, localized between inner and outer photoreceptors (IS/OS junction) and the RPE, may seem potentially interesting from the point of view of future diagnostics. Making use of the fact that OCT signal coming from these structures is relatively strong, specific measurement protocols and a number of image analysis methods may be created, which will allow for a quantitative analysis of photoreceptors and RPE. A detailed assessment of this area may be significant in clinical practice, because many of the degenerative retinal diseases emerge in close proximity to the RPE. Recently, a couple of studies have been published that deal with the analysis of posterior retinal layers, proposing the reconstruction of their thickness map, RPE topography and IS/OS topography, as well as reflectivity maps of these layers [100, 101, 102, 103, 104, 105]. Figure 12 shows results of quantitative assessment of outer retinal layers based on 3D OCT data measured in the eye of a patient with large confluent drusen. In this case, the shape of the drusen is regular, creating oval elevations on topographical maps. Thickness maps show that the average distance between RPE and IS/OS is decreased in places corresponding to the top of the drusen (blue color on IS/OS-RPE thickness maps). On the other hand an increase of these distances is visible in the basal part of the drusen, and this probably points to mechanical “stretching” of IS/OS by the elevated drusen. A significant advantage of the presented analysis is the possibility of a quick assessment of the evolution of disease progression. In this case both topographical maps enable a localization of drusen distribution and quantify their elevations. Such an analysis may be valid in the case of AMD and degenerative changes of photoreceptors or retinal detachments [104].

An application of the high-speed OCT instruments to the anterior segment OCT imaging is especially interesting, since it might have the potential to provide significant complementary information either on particular anatomical details or a large scale architecture of the cornea, iris, and crystalline lens. The first can be useful in ophthalmic diagnosis for detailed monitoring of the corneal epithelium, Bowman’s membrane, stroma, capsule of the crystalline lens, intraocular lens surface, conjunctiva, or the corneo-scleral junction (Fig. 13). Similarly to retinal applications improved imaging quality offered by high-speed FdOCT instruments enables visualization of localized pathological changes in the anterior segment and provides data on corneal thickness and opacity [106, 107, 108, 109, 110]. Meanwhile, the large scale imaging covering the depth of 5mm and 15mm×15mm of the transverse range enables one to give morphometric parameters including the corneal thickness and topography, corneo-scleral angle, orientation of intraocular lenses, etc. OCT imaging of the anterior segment of the human eye requires significantly different measurement conditions compared to retinal OCT. The biggest challenge here is the requirement of collecting data from a much larger volume than in the case of retinal OCT.

In order to get all information about the entire cornea including the corneo-scleral junction and the anterior surface of the crystalline lens a volume of approximately 15mm×15mm transversally and 5mm in depth has to be scanned. Thus, if we keep relatively high axial resolution and high scanning density the size of data to be captured with the acquisition system and stored in the hard drive will increase significantly. For example to obtain imaging with a transverse resolution of 20μm symmetrically in both directions, an axial resolution of 3μm and assuming more than 8  bit analog-to-digital conversion 4.5GB of data has to be collected. In practice this has to be done during a time short enough (less than 1 s) to minimize motion artifacts.

These requirements are highly demanding for both: optical detection and digitalization/ transfer to PC. To meet the above-mentioned specifications an ideal OCT instrument should run with more than 560,000 A-sans/s to collect high-resolution volumetric data from the entire anterior segment within 1 s. Recently two complementary high-speed OCT instruments dedicated to anterior segment imaging based on spectral and swept source OCT have been demonstrated [26, 40]. The first of them using CMOS based spectrometer enabled imaging with adjustable speeds up to 135,000 A-scans/s with variable axial resolution (dependent on number of CMOS pixels used) and constant axial range of 5.2mm in tissue and 10mm in complex spectral OCT mode [26]. Another high-speed instrument based on swept source technology running up to 200,000 A-scans/s with a custom designed 1300nm FDML swept laser was also reported [40].

The main advantage of the 800nm anterior segment SOCT instrument is its higher sensitivity for low-scattering structures such as the cornea or crystalline lens. Figure 14 shows examples of high- quality cross-sectional images of the cornea with the entire anterior chamber and the crystalline lens. It is also possible to apply a more elaborate full range, complex OCT technique to extend the axial field of view and visualize the entire anterior segment with cornea and crystalline lens in one cross-sectional image [Fig. 14b]. On the other hand the main advantage of the swept source instrument in turn, is its higher scanning speed and flexibility. Existing swept source OCT instruments allow for fast and convenient adjustment of working parameters (axial resolution and measurement range) to operate in different programmable regimes by setting the value of the filter driving signal amplitude. Moreover, due to reduced sensitivity drop-off it is possible to acquire large scale 3D images of the anterior segment (Fig. 15).

High-speed FdOCT instruments enable also 4D imaging (3D in time). Such approach offers an opportunity to monitor anterior segment of the eye during dynamic changes. An example of 4D imaging is shown in Fig. 16, where the entire 3D scanning protocol was repeated in time, giving real-time volumetric reconstruction of the anterior segment with contracting iris in response to light stimulus [26, 40].

One of the most important aspects of using high-speed detection for corneal imaging is quantitative analysis of the cornea’s thickness and topography. HIgh-speed detection is especially useful for diagnosis of diseases, precise location of lesions, and planning of medical and surgical treatments. The remarkable advances in the field of refractive surgery have increased requirements for more accurate imaging and measurements of corneal curvature and topography. Relatively new imaging systems, such as scanning slit topography, rotating Scheimpflug imaging, and ultrasound biomicroscopy are being applied for this purpose [111]. Commercially available systems (Orbscan, Pentacam) enable measuring thickness of the cornea and contour and shape for its both surfaces. However, due to insufficient acquisition speed these instruments provide images with low sampling density. In the case of a quantitative analysis of the corneal geometry it must be also considered that due to the fixation lag some misalignment between an eye and the instrument may occur [112]. As a result, the cornea may be translated and rotated in the 3D space, which will strongly influence its topographical representation. In order to perform an effective correction, misalignment data should be collected in 3D with the use of a raster scanning protocol and with reduced influence of motion artifacts.

A swept source OCT instrument with imaging speed of 200,000 A-scans/s demonstrated by Gora et al. enabled acquiring 3D datasets within 250ms with sampling density sufficient for quantitative analysis of the anterior segment of the eye [113, 114]. An analysis including reconstruction of corneal topography elevation best fit sphere and thickness maps based on dense raster scan OCT data with a reduced number of motion artifacts was demonstrated for a normal eye and an eye with a pathology (Fig. 17).

4B. Other Biomedical Applications

Large scale 3D imaging can be also significantly beneficial for endoscopic and laparoscopic applications [37, 115, 116]. In these applications the main task of OCT imaging is examination and screening for early neoplastic localized changes in large luminal surface areas. In contrast to excisional biopsy high-speed OCT imaging has the potential of providing the ability to survey large tissue volumes in real time. Figure 18 shows an example of Fourier-domain, swept source OCT images of the porcine distal esophagus in vivo published by Vakoc et al. [117]. This example shows that it is possible to image the entire mucosal thickness over 360° with full 4.5cm pullback length, with a resolution approaching that of histopathology. The transverse cross-sectional image in Fig. 18b and reconstructed longitudinal cross- sectional image in Fig. 18c show the mucosal microscopic structure, which can be reconstructed over the entire imaged volume.

A similar challenge of large scale imaging while searching small focal (localized) regions is also inherent in the field of cardiology. The main task of the OCT imaging would be here to understand coronary atherosclerosis and to monitor the response to intravascular interventions such as implementation of stents or angioplasty. Three-dimensional and high-speed imaging can help significantly in better understanding factors associated with heart attack and to develop the deployment of better therapeutic strategies. Another important challenge in intravascular imaging is associated with high scattering and absorption of the blood, which makes it almost perfectly opaque for near-infrared light [37, 38]. The only way to analyze the structure of vascular wall is to occlude flow or to displace blood through the injection of a transparent liquid such as saline. However, such procedure can be applied for only a few seconds without risk of ischemia. Previous intravascular OCT imaging with TdOCT enables one to obtain high-quality tomograms, but since the acquisition rate was limited to a few frames per second, only small longitudinal sections within the coronary arteries could be visualized. The recent developments of new Fourier-domain detection schemes for OCT has overcome this limitation by increasing imaging speeds to more than 100 frames/s. A group from the Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, has shown unprecedented comprehensive intracoronary imaging in human patients [38]. These studies were possible with a high-speed swept source OCT instrument performing imaging after a brief, nonocclusive injection of saline through a guiding catheter. Figure 19 shows example of a large scale 3D intravascular imaging in vitro using commercial prototype device constructed by LightLabs using high-speed FDML laser swept source.

Another interesting field demonstrating capabilities of high-speed OCT imaging is developmental biology. The understanding of formation of functional organs requires observation of dynamic changes in the cellular architecture. The ability to directly image these complex morphogenetic movements can greatly enhance our understanding of normal development as well as congenital abnormalities in live model systems. Recently, a group from University of Houston demonstrated that OCT is likely to offer the best compromise between spatial resolution and depth penetration of any available method for imaging of live mammalian embryos [74, 118, 119].

This group demonstrated data obtained with a laboratory swept source OCT instrument using a broadband swept-source laser (Thorlabs, SL1325-P16) with output power P=12mW at central wavelength λ0=1325nm and spectral width Δλ=110nm that gives in-depth resolution of 6μm in tissues. The scanning rate over the full operating wavelength range is 16kHz [74]. Figures 20a, 20b, 20c, 20d show examples of 3D reconstructions of embryos at different stages of development. High spatial resolution of 6μm provides an insight into details of many easily recognizable structural features, such as the heart and a region of the vitelline vein of the live embryo at the 8.75 days post coitum (dpc) stage. The acquisition was performed at 128  A-scans/frame with an acquisition rate of about 60 frames/s. High-speed OCT instruments have a potential of studying early embryonic hemodynamics by tracking of individual blood cells, which are visible in the vitelline vein (labeled by red arrows) and the heart [Fig. 20e].

The tracking of individual blood cells in embryonic heart has been also demonstrated by Jenkins et al. for avian embryos, which are an important model for studying cardiac developmental biology [120, 121]. For this purpose the authors applied an optical coherence tomography (OCT) system using a buffered FDML laser allowing for imaging with high speed at 100,000 A-scans/s. The high scan rate enables the acquisition of high temporal resolution 2D datasets (195 frames/s or 5.12ms between frames) and 3D datasets (10 volumes/s) ,demonstrating spatiotemporal details of cardiac motion not resolvable using previous OCT technology.

Results presented by Jenkins et al. obtained with high-speed OCT show embryonic quail heart imaged in 4D without the aid of gating. For the first time to our knowledge the heart has been viewed in cross-section during looping with extremely high temporal resolution, enabling the observation of morphological dynamics of its beating (Fig. 21). The embryonic heart at stage 10 had just begun to beat. Application of high-speed OCT imaging with Fourier-domain detection enables one to observe the time-dependent distribution of individual red blood cells in the earliest stages of development, with an apparent increase in number as the embryo developed.

5. Physiological and Functional OCT Imaging

As was demonstrated above, application of high-speed FdOCT to structural imaging in ophthalmology, laparoscopy, endoscopy, cardiology, and developmental biology has many positive implications for science and clinical practice. However, the natural step in the development of any biomedical imaging modality is an effort to search for additional information associated with the function of the imaged structure supplementary to its morphology. Such defined OCT functional imaging can be especially important in medicine for early diagnosis of diseases before any morphological symptoms occur. It can be also be a very practical tool for basic medical and biological studies. High-speed OCT is especially suitable for such studies, with its high spatial resolution, high sensitivity, and noninvasive operation. OCT as an optical modality can measure additional physical quantities characterizing light scattered back from the sample such as spectral intensity distribution, change of the polarization state, modulation of Doppler effect in optical frequency, and a phase shift of interferometric signals. This information in turn can be used for determination of tissue properties associated with its function such as depth-resolved extinction indicating for example blood oxygenation, flow velocity indicating blood perfusion, birefringence indicating organization of tissue fibers, and sample reflectivity indicating neuronal activity. All of these quantities have been measured with TdOCT systems showing additional potential of OCT technology either for functional imaging or for improvement of imaging contrast [3, 4]. However, most of these studies were not applicable for in vivo studies due to slow speeds offered by TdOCT. Progress in high-speed FdOCT has opened new perspectives for functional OCT imaging, which in fact can be verified and developed only by running in vivo experiments.

5A. High-Speed Doppler OCT

Blood perfusion has attracted attention as a potentially important physical parameter for functional studies. OCT can help to determine a longitudinal flow velocity (velocity parallel to the probing beam) by looking at a Doppler frequency shift Δω introduced to interference fringes by light backscattered from a moving particle interfering with the reference beam. The frequency shift can be found separately for each depth location in the sample. In TdOCT the Doppler optical frequency shift can be obtained by analysis of the power spectrum of the measured fringe signal using either a short-time fast Fourier transform or a wavelet transformation applied to a digitized fringe signal [122, 123, 124, 125]. The velocity sensitivity of this method is strongly limited for higher speeds and resolution due to limitations in sampling rates in analog-to-digital converters. To overcome this problem the phase-resolved technique was developed, which helps to decouple spatial resolution and velocity sensitivity in flow analysis. This method is based on linear relationship between the phase difference of consecutive spectral fringe signals and the velocity of the moving sample. Application of phase-resolved velocity measurements in TdOCT allows one to increase imaging speed by more than two orders of magnitude without compromising spatial resolution or velocity sensitivity [126, 127].

The direct measurement of the Doppler frequency shift cannot be performed using the basic configuration of the FdOCT setup. Therefore, the first choice for velocity measurement by SOCT and swept source OCT was the phase-resolved method [128, 129, 130, 131].

A very spectacular example of the phase-resolved OCT technique applied to measurements of tumor angiogenesis, lymphangiogenesis, tissue viability, and both vascular and cellular responses to therapy has been demonstrated recently by Vakoc et al. [132]. The authors of this publication introduced swept source OCT (OFDI) as an intravital microscope along with a confocal multiphoton microscopic device using the phase variation of OCT signals as an intrinsic contrasting mechanism to explore physiological processes in solid tumor biology in vivo.

Use of high-speed Fourier-domain detection combined with the phase-resolved optical velocity measurements enabled also for the first time to create volumetric maps of longitudinal component of retinal blood velocity. Such results were demonstrated by Schmoll et al. (Fig. 22) [133]. In this contribution authors demonstrated the high-speed spectral OCT instrument using CMOS detector achieving high speed of imaging up to 100,000 A-scans/s applied for velocity measurements. The authors showed maps of the retinal blood flow near the region of optic disc of human eye in vivo. Adjustable speeds of OCT signal registration made it possible to extend the range of measured velocities, as a result revealing different vascular structures corresponding to different exposure times (Fig. 22).

Another spectacular result of phase-resolved velocity estimation by swept source OCT system has been demonstrated by Mariampillai et al. [75]. They combined the retrospective gaiting technique with the high-speed swept source OCT instrument. The optical cardiogram gating technique introduced by Yazdanfar in 1997 [134] for TdOCT enables one to increase significantly the effective frame rate of phase-resolved OCT.

This technique was applied to imaging periodic motion in the cardiovascular system of embryos allowing for ultrahigh-speed visualization of the blood flow pattern in the developing hearts of African clawed frog embryos (Xenopus laevis). Introduction of high-speed FdOCT imaging enabled obtaining 4D (three spatial dimensions + temporal) Doppler imaging at 45 frames/s, providing detailed visualization of the complex cardiac motion and hemodynamics in a beating heart (Fig. 23).

Recently, a group from the University of Houston has demonstrated phase-resolved optical velocity measurements of individual circulating blood cells in live mammalian embryos also using swept source OCT instrument but without a gating procedure [119]. In their experiments it was possible to track individual blood cells since the majority of blood cells remain still restricted in blood islands for early stages of embryonic development. Figure 24 shows a structural image of a fragment of an embryo containing dorsal aorta and corresponding color-coded Doppler velocity maps acquired at different phases of the heartbeat cycle from the same area of the embryo.

The phase-resolved FdOCT technique has strong limitations in velocity recovery in the presence of motion artifacts and low SNR [129, 130, 131, 135], which both are typical for in vivo OCT biomedical imaging. To avoid an influence of these two factors novel methods of extraction of Doppler information have been proposed. The first called resonant Doppler imaging has been introduced by Bachmann et al. [136]. This technique determines flow velocities by using intensity information without the need for extracting the signal phase. It is based on the effect of interference fringe wash-out that occurs when the path difference between structure and the reference mirror changes during camera integration. In their experiments an electro-optic phase modulator in the reference arm was driven with specific phase cycles locked to the Doppler frequency of the sample flow. For this reason the signals of blood flow can be enhanced, whereas the signals of static structures are suppressed. Resonant Doppler FdOCT requires a complex optical setup and precise synchronization, however it operates without an elaborate signal processing algorithm. Another interesting method of 3D visualization of blood perfusion was proposed by An and Wang [137, 138, 139]. This technique, called optical microangiography, enables one to separate the moving and static components within a sample by introducing a constant modulation frequency to a standard SOCT measurement. In this method, Doppler shifts originating from moving particles greater than the introduced modulation frequency can be identified and used to segment vessels. This concept, called BM-mode scanning [140], was initially introduced to SOCT by Yasuno et al. in 2006. This technique, similar to optical coherence angiography and scattering optical coherence angiography proposed by Makita et al. [141, 142], enables one to map only the blood vasculature without providing quantitative information about the longitudinal flow velocity. Another velocity-resolved flow imaging technique has recently been proposed by Tao et al. This method called single-pass flow imaging spectral-domain OCT [143, 144] uses a modified Hilbert transform and spatial frequency analysis to obtain a stack of depth- resolved images, each representing a finite velocity range.

In order to measure directly optical frequency shift (Doppler signal) by FdOCT it is necessary to modify the measurement protocols and to acquire multiple times spectral fringe signals for the same (or very close) transverse position of the scanning beam.

This method, called joint spectral and time-domain OCT (STdOCT), has been proposed by Szkulmowski et al. [145, 146]. In this technique spectral fringes measured with high lateral oversampling are arranged into subsets. One subset creates 2D inter ferogram representing a set of time-dependent interferometric fringes. The Doppler frequency shift Δω introduced by a particle moving within the sample will correspond to a modulation frequency of the signal analyzed along the time axis of the 2D interferogram. Application of 2D Fourier transformation provides simultaneous reconstruction of the longitudinal component of velocity and the axial position of the moving particle (Fig. 25).

The main advantage of this technique is relatively simple and time-efficient data processing. It has been also proved that STdOCT as compared to phase- resolved OCT, offers higher sensitivity and better reliability in quantitative velocity estimation in the entire velocity range [145]. STdOCT technique has been also applied to reconstruct volumetric maps of flows and segmentation of retinal and choroidal vasculature in vivo (Fig. 26) [70]. These measurements were performed using SOCT instrument with axial resolution of 2.3μm and a CMOS detector running up to 115,000 A-scans/s. The STdOCT method is a good example of how new, functional information can be extracted uniquely by the application of high-speed FdOCT instrument. Performing multiple OCT measurements in fractional time compared to standard structural imaging does not influence the OCT morphologic reconstruction since all A-scans in the subset can be averaged, resulting in the same total exposure time and sensitivity. But here the fractional data can be additionally processed to get true Doppler information.

5B. Optical Measurements of Neural Physiology

One method of measuring neural activity is an application of the phase-sensitive method, which has the ability to range very small displacements or motions of nerve bundles on the picometer to nanometer scale [147, 148, 149]. According to Hill [150] there are two suggested mechanisms responsible for a shrinkage of the neurons observed with repetitive stimulation. The first says that the difference in hydration may shrink the nerve at the beginning of repetitive excitation and the subsequent rate of swelling depends on membrane permeability to water. In the second explanation, the nerve swelling is due to chloride and sodium transfer to the fiber caused by a sudden increase in sodium permeability. Then the nerve fiber will shrink in the presence of unbalanced hydrostatic pressure [147]. One of the main advantages of SOCT is its high phase stability. Therefore, this technique is very well suited for phase-sensitive measurements of neural swelling as was demonstrated by Akkin et al. [151]. Application of high-speed OCT instruments has the advantage of reducing motion artifacts and enabling changes to be measured on the millisecond timescale.

Another idea behind the optical measurements of neural physiology is to observe small, intrinsic changes in optical properties of tissue caused by its neural activity. Objective assessment of such functional changes in vivo that is accessible for clinical practice would be a powerful tool for early diagnostics and monitoring disease progression and response to therapy. It could be also a very useful method for basic medical and biology research for elucidating pathogenesis of disease. If successful, these methods could enable quantitative measurement of functional response as well as 3D mapping of response across the measured object. Change of optical properties of the brain cortex due to the membrane depolarization and cell swelling has been demonstrated by Grinvald et al. in 1988 [152] and by Villringer et al. in 1997 [153]. Early research on OCT imaging of neural activity based on analysis of scattering changes in the cat visual cortex [154, 155] as well as in the sea slug ganglion [156] has been presented.

Functional OCT has the potential to be an objective and highly specific tool for measuring neural function especially in the retina. Studies using fundus reflectometry and flash stimuli have demonstrated retinal reflectance changes that may be indicative of retinal function [157, 158, 159, 160, 161, 162]. However, in these studies a total light scattered back from the fundus is measured, resulting in a high level of a background noise. OCT provides fine depth discrimination and potentially can improve the sensitivity of small reflectivity change measurements by choosing a single layer inside the tissue. The first research work in retinal activity was conducted by Bizheva et al. using conventional TdOCT [163]. It demonstrated measurement of retinal functional changes in response to a flash stimulus of ex vivo retinal preparations from rabbits [163]. These studies showed changes in OCT backreflected intensity from individual retinal layers, including the photoreceptor and plexiform layers. Reflectivity changes were also correlated with the measured ERG response. The observed variations of the retinal reflectivity were attributed to photoreceptor disc membrane hyperpolarization in response to a strong stimulus.

In vivo functional OCT measurements are challenging because the speckle noise in the presence of the object motion can cause time-dependent variation of the sample reflectivity. This problem is severe since the speckle size is on the order of magnitude of single micrometers. High-speed data acquisition offered by the OCT with Fourier-domain detection promises to enable an application of sophisticated signal registration or online tracking techniques. The latter can help detect small changes of the object position caused by its involuntary movement and eliminate the strong influence of speckle noise. Preliminary results demonstrating applicability of high-speed OCT detection for noninvasive in vivo functional optical imaging of the intact retina of animal model have been demonstrated by Srinivasan et al. [164]. In these experiments imaging was performed with 2.8μm resolution at a rate of 24,000 A-scans/s.

To correct motion artifacts 3D volumes of 160μm×160μm×1200μm corresponding to 64×64×1024 pixels were acquired repeatedly with a raster scan pattern in 162ms (6.2  volumes/s). Then the transverse eye motion artifacts were corrected by cross correlation and cropping of consecutive data sets. The presented experiments showed a significant 10%–15% increase in the average amplitude reflectance of the photoreceptor outer segments as a response to a white-light stimulus [Fig. 27a]. A very important outcome of these studies was the observation that reflectance change was largest in the region between the photoreceptor IS/OS junction and the RPE [Fig. 27b].

The eventual goal of this research is to develop techniques for functional imaging studies in human subjects. Recent work in the field of scanning laser ophthalmoscopy with adaptive optics demonstrated the ability of tracking fast physiological processes in single photoreceptor cells in the living human eye based on reflectivity variations [165, 166]. Recently Srinivasan et al. repeated experiments measuring intrinsic signals in normal human eyes in vivo [167]. Also other groups demonstrated preliminary results of in vivo retinal OCT reflectometry in human eyes [168]. However, to our knowledge conclusive results have not yet been provided. The main reason is probably the negative influence of eye motions. In order to achieve more reliable measurements of retinal intrinsic signals and eventually perform clinical studies it is still necessary to increase imaging speeds or to introduce very precise eye tracking. Another important issue is the lack of deep understanding of the physiology that produces intrinsic optical signals. Without this knowledge it is difficult to optimize the stimulus and measurement protocols. Probably future in vitro measurements and work with animal models will help identify parameters that are most likely to yield a relevant optophysiological analysis.

Experiments conducted by Srinivasan and others have proved a direct relationship between reflectivity of IS/OS junction and neuronal activity of photo receptors. Based on these observations one can conclude that also in pathological cases of photoreceptor disorders it should be possible to distinguish between neuronal active areas from this without activity by looking at the reflectivity maps of IS/OS junction extracted from 3D OCT data. Such clinical experiments were demonstrated by Sikorski et al. in the case of a rare multifocal inflammatory condition involving the retina called multiple evanescent white dot syndrom (MEWDS) [100]. In this retinal disease, first described in 1984 by Jampol et al., patients experience acute, painless, unilateral loss of vision. The disease is self-limiting, with almost all patients regaining good visual acuity within several weeks.

The pathogenesis of MEWDS is still unknown, but there is a probability of an infectious or autoimmune etiology of the disease. An interesting outcome of studies presented by Sikorski and co-workers is that during the acute stage of MEWDS the reflectivity map of the IS/OS junction displayed areas of reduced reflectivity that showed a strong positive correlation with hypofluorescent ICGA spots and with hyperfluorescent fluorescein angiography dots, while other retinal layers did not reveal any reflectivity changes (Fig. 28). There is a high probability that the dramatic loss of vision during the acute stage of the disease is time dependent, and focal pathologic changes occurred before any morphological symptoms appeared. Therefore, this case can be treated as a good model to demonstrate an idea of functional optical measurements of neural physiology in clinical conditions.

5C. Spectroscopic OCT

Spectroscopic analysis of light reflected back from the measured object can provide information about its morphology and physiology. Early spectroscopic investigations with dual-wavelength OCT imaging using two superluminescent diode light sources demonstrated measurement of water absorption and concentration [169, 170]. The first attempts at using spectroscopic TdOCT with broadband femtosecond Ti:sapphire lasers for biological object was demonstrated by an MIT group in 2000 [171]. Later studies conducted by Faber et al. were focused on applications of SOCT to measurements of hemoglobin oxygenation [172, 173]. Quantitative analysis of optical properties in scattering media has also been investigated [173, 174]. SOCT using Fourier-domain detection was demonstrated in 2000 [175]. This method offers a significant advantage for SOCT by enabling direct access to the spectrum. Preliminary results of using broadband light sources such as supercontinuum light with SOCT has been demonstrated recently [176].

Surprisingly, in all of these publications the authors neglected an influence of effects of random light modulation caused by diffusive reflections of probing beam components within the turbid media. This effect strongly limits the SOCT technique by introducing a specklelike pattern to spectral envelopes reconstructed by OCT. In this case it is impossible to extract undisturbed spectroscopic information without averaging large volumes of data. Instead application of advanced filtering methods can generate relatively smooth but random curves, which can be treated as a real absorption characteristics. Another important limitation of SOCT is that the spectral envelopes measured in SOCT result from a combination of scattering and absorption integrated over the path of light propagation. Therefore, only the extinction curve can be reconstructed directly from OCT data.

Recently Tamborski et al. have proposed a method for simultaneous retrieval of extinction and Doppler information with high-speed FdOCT [177]. In that paper the authors proposed to measure the extinction coefficient in the presence of sample motion for example in blood vessels. Such motion can efficiently reduce the speckle contrast and increase the efficiency of speckle averaging. Another advantage of the proposed technique is that the same measurement protocol can be applied to calculate flow velocity using joint spectral and time-domain OCT techniques. Figure 29 shows an example of retrieval of the spectral envelope in retinal blood vessels along with the Doppler analysis. Figure 29c demonstrates the effect of the random modulation of spectral envelope caused by the Fourier-domain speckle pattern, which is still present even for averaging of 2000 A-scans corresponding to a transverse distance of approximately 200μm.

6. Conclusions

A great increase in the number of OCT investigations has taken place during the past 5 years, in parallel with the development of Fourier-domain OCT technologies that have opened new frontiers of OCT application. The most crucial is the significant improvement of speed, enabling the rapid acquisition rates that are necessary to reduce artifacts introduced by patient motions. Due to high speed, in vivo 3D volumetric imaging on large scales within reasonable time limits is now possible. At present the most widely used FdOCT techniques are specral OCT and swept source OCT, which are at present covering the broadest range of applications. They also can be optimized within the framework of currently available technology of detectors and wideband light sources. Another important factor influencing the rapid development of these two methods is their ability to make use of novel modalities targeted to enhance imaging contrast such as polarization-sensitive OCT [178, 179, 180, 181, 182, 183], molecular fluorescent OCT imaging [184, 185, 186, 187, 188], and second-harmonic OCT [189, 190]. Finally these methods can be easily combined with other imaging or functional techniques, enabling creation of new multimodal platforms that can provide more valuable information about measured tissue.

It has to be noted that FdOCT has intrinsic limitations such as sensitivity drop-off, presence of coherence noise terms, and lower dynamic range [69]. There are also differences in performance among various FdOCT techniques, including SOCT, swept source OCT, chirped OCT [190], and demultiplexer-OCT. Each of these techniques as well as other TdOCT methods has its own advantage and can be preferred for a certain application. For example in ophthalmology, the favorite wavelength window for imaging is centered at 800nm because of the relatively low absorption in the anterior chamber and vitreous at this wavelength. It is likely that SOCT will remain dominant in ophthalmic applications since the development of rapidly swept lasers at 800nm is limited due to the lack of efficient and robust ASE sources and additional constraints of dispersion and losses in optical fibers. In the case of endoscope-based or catheter-based OCT imaging, 1300nm seems to be still ideal due to larger imaging penetration within tissue and low cost of fibers at these wavelengths.

Another factor differentiating SOCT and swept source OCT is phase stability. In SOCT instruments interferometric fringes are detected in parallel, hence the phase constancy depends only on the mechanical stability of the interferometer. In swept source lasers additional phase jitter can occur since the phase of the registered interferometric signal is changed by mechanical filtering of optical frequency components in the laser cavity. Additionally, these systems can suffer from instabilities of the laser action due to cavity oscillations and multimode operation in short cavity setups or fiber instabilities in the FDML instruments. Therefore, highly demanding phase-sensitive techniques such as ultrasensitive phase-resolved OCT microscopy [54, 192] will exhibit better performance when SOCT is used. Also the consideration in selecting between the two platforms can be still dependent on the resolution requirements—basically with shorter optical wavelengths one can achieve better axial resolution. It will be still challenging to construct swept sources for visible range. Probably in the near future ultrahigh-resolution SOCT systems working in the visible range will be explored more due to significant progress in supercontinuum light technology. One of the future challenges is in fast data processing and new algo rithms for image processing, which can deliver more reliable and clinically significant information. Also high-speed systems provide a huge amount of data that should be handled online.

Looking further into the future there is high probability that OCT instruments will achieve a speed of more than 1,000,000 A-scans/s. These improvements will enable a wide range of new imaging and measurement protocols, which promises to greatly enhance the ability to visualize biomedical objects. There will also be the possibility to extend OCT applications to other fields such as art conservation [193, 194] and industrial inspections [195]. An achievement of megahertz imaging rates should also open new perspectives for further development of optical coherence imaging techniques, enabling enhanced imaging contrast, providing molecular sensitivity, and making available functional imaging. Finally there is a hope that in the long term further development of high-speed coherence optical methods will help to accomplish the original goal of OCT technology of performing noninvasive optical biopsy at the cellular level in vivo.

The author would like to acknowledge Prof. Andrzej Kowalczyk head of the Medical Physics Group at NCU, Toruń, Poland; Prof. James G. Fujimoto from Massachusetts Institute of Technology, Cambridge, USA; Prof. Adolf F. Fercher and Rainer Leitgeb from Medical University of Vienna, Austria; my colleagues from the Medical Physics Group at NCU; Krzysztof Stefański, Piotr Targowski, Maciej Szkulmowski, Michalina Góra, Iwona Gorczyńska, Sławek Orłow ski, Anna Szkulmowska, Karol Karnowski, Daniel Szlag, Danka Bukowska, and Szymon Tamborski; Bartosz Sikorski, Jakub Kałużny, and Bartłomiej Kałużny from the Ophthalmic Clinic at Collegium Medicum NCU; Jay S. Duker and Andre Vitkin from the New England Eye Center, Boston, USA; Vivek J. Srinivasan from Harvard University; Robert Huber from Ludwig Maximilians University in Munich, Germany; Yoshiyaki Yasuno from the University of Tsukuba, Japan; Susana Marcos from Consejo Superior de Investigaciones Científicas, Madrid, Spain; Robert Zawadzki from the University of California, Davis; Bill Ahern from Axsun Technologies; Tomasz Bajraszewski from Optopol Technology; and Kevin Hsu from Micron Optics. Contributions from other groups: Brett E. Bouma, Benjamin Vakoc, Guillermo J Tearney at the Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School; Robert Huber, Ludwig Maximilians University, Munich, Germany; James G. Fujimoto at MIT, Kirill Larin at the University of Houston; Alex Vitkin at the University of Toronto; Rainer A. Leitgeb at Medical University of Vienna; and Andrew Rollins at Case Western University are highly appreciated.

This work was supported by the European Heads of Research Councils (EuroHORCs), European Science Foundation, and Foundation for Polish Science within the framework of EURYI Award EURYI-01/2008-PL as well as by the Polish Ministry of Science and Higher Education (research grants for years 2005–2008 and 2006–2009).

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Table 1. Comparison of Signal and Noise Components, Sensitivity, and Dynamic Range for TdOCT and FdOCTa

 

Fig. 1 Simplified block diagram of the TdOCT method.

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Fig. 2 Illustration of A-scan formation in FdOCT. Besides the A-scan corresponding to the structure, the resultant signal also includes a conjugate symmetrical image and coherence noise terms. Additionally all signals are affected by the sensitivity drop-off caused by the limited spectral resolving power of OCT spectrometers or the finite instantaneous linewidth of light emitted by a rapidly tunable laser.

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Fig. 3 Block diagrams of the OCT methods with the use of Fourier-domain detection: (a) spectral (spectral domain) OCT (SOCT), (b) swept source OCT (OFDI).

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Fig. 4 Sensitivity as a function of the reflectivity of the reference mirror for the SOCT system with a complementary metal oxide semiconductor camera with exposure time Texp=4μs and for a swept source OCT instrument without dual-balanced detection with corresponding exposure time Texp=12μs. In both cases the measured optical power on the sample P=1mW. The solid green line corresponds to theoretically calculated sensitivity. The solid blue, red, and black lines represent separately contributions of shot-noise, RIN, and read-noise components.

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Fig. 5 Progress in high-speed OCT technology. The graph demonstrates arbitrarily chosen, representative milestones in the OCT speed development: the instruments are blue, TdOCT; red, SOCT; green, swept source OCT.

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Fig. 6 Comparison of OCT cross-sectional imaging of the human eye in vivo: (a) time-domain detection, image obtained with the use of a commercially available OCT 3 Stratus (Zeiss) device, which enables imaging with an axial resolution of approximately 10μm and speed allowing for acquiring 400 optical A-scans per second; (b) Fourier-domain detection, image obtained with the use of a laboratory device that enables imaging with an axial resolution equal to 2μm and speed allowing for a measurement of 30,000 optical A-scans/s.

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Fig. 7 High-quality cross-sectional retinal imaging: (a) Fundus photography with a line indicating the location of the transverse OCT scan shown in (c). (b) OCT cross-sectional image of outer retinal layers including external limiting membrane (ELM), junction between inner and outer segments of photoreceptors (IS/OS) and the RPE-enlarged region from (c). (c) High-quality panoramic OCT image scanned along the pappilomacular axis acquired with the registration speed equals 30,000 lines/s.

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Fig. 8 High-quality clinical retinal cross-sectional imaging of retinas with AMD: (a) nonexudative AMD with soft drusen, (b) exudative AMD with neovascular membrane and fibrous scar, (c) nonexudative AMD along with large confluent drusen.

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Fig. 9 High-quality clinical retinal cross-sectional imaging using high-speed SOCT instrument: (a) full thickness macular hole, (b) central serous chorioretinopathy in acute stage, (c). photoreceptor dysfunction in a patient with acute zonal occult outer retinopathy.

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Fig. 10 (a) Diagram of creating the image of the eye’s fundus from data obtained by 3D OCT. (b) Illustration showing retinal reflectivity maps of chosen layers from 3D OCT: NFL, nerve fiber layer; IS/OS, junction between inner and outer segments of photoreceptors; RPE, retinal pigment epithelium.

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Fig. 11 Three-dimensional OCT imaging of human optic disc in vivo along with a quantitative analysis of the nerve fiber layer (NFL) thickness.

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Fig. 12 Quantitative analysis of outer retinal layers based on 3D OCT data in case of confluent drusen in 61 year-old patient’s eye. Zoomed inset indicates the localization of segmented layer consisting of outer segments of photoreceptors and RPE. Measurements performed after 12 months indicate a significant dynamics of the disease progression, which can be determined quantitatively by direct comparison of RPE topography and/or IS/OS topography maps.

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Fig. 13 High-quality, ultrahigh-resolution (3μm in tissue) cross-sectional imaging of the anterior segment of the human eye in vivo with 800nm SOCT instruments: (a) cornea, (b) corneo-scleral angle, and (c) anterior part of the crystalline lens. (Courtesy of Tomasz Bajraszewski, R&D Optopol Technology/images obtained by the prototype SOCT Anterius instrument.)

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Fig. 14 High-quality, ultrahigh-resolution cross-sectional in vivo imaging of the anterior segment of the human eye measured by 800nm high-speed spectral OCT instrument with CMOS detector: (a) corneal imaging, (b) crystalline lens, (c) full range complex SOCT of the anterior segment of the human eye.

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Fig. 15 Large scale OCT imaging of the anterior segment of the human eye in vivo. Volume rendering from data acquired by a table top swept source OCT instrument using 1300nm tunable laser (Axsun Technologies) with 50,000 A-scans/s.

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Fig. 16 Four-dimensional OCT imaging using high-speed 800nm, SOCT instrument: consecutive volume renderings of anterior segment of the human eye during pupillary contraction, volume size 300×100×1024 pixels corresponding to 5mm×15mm×15mm.

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Fig. 17 Volume rendering of 3D OCT data of anterior segment in vivo: (a) normal eye, (c) eye with keratoconus. Results of the quantitative corneal analysis of normal eye (b) and the eye with keratoconus (d) are shown. The posterior surface of the pathologically changed cornea is highly conical, and the apex of this surface is shifted to the left with respect to the anterior surface. An aspherical shape of both the anterior and posterior surfaces may be identified on the elevation maps by the regions characterized by large values of the distance between the corneal surface and the fitted sphere.

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Fig. 18 High-speed large scale imaging of porcine distal esophagus in vivo: 3D renderings of the distal esophagus with quadrant cutouts and planes designating the locations of the cross-sectional images. (Courtesy of Brett Bouma and Ben Vakoc; Image reprinted from Vakoc et al. [117] with permission of the American Society for Gastrointestinal Endoscopy.)

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Fig. 19 Volumetric ex vivo imaging of a human radial artery (bypass graft segment) using an FDML laser operating at 45 kHz, 80  frames/s, 10mm/s longitudinal scan rate. (Courtesy of Joseph Schmitt, Lightlab Imaging.)

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Fig. 20 Structural imaging of early embryos with swept source OCT. (a)–(c) Three-dimensional reconstructions of live embryos with the yolk sac at 7.5dpc, 8.5dpc, and 9.5dpc, respectively. (d) Three-dimensional reconstruction of 10.5dpc embryo. (e) Live imaging of a heart and a fragment of a vitelline vein with individual circulating blood cells (labeled with arrows) at 8.5dpc. (Courtesy of Kirill Larin, University of Houston.)

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Fig. 21 High-speed OCT of (a)–(c) stage 10–12 from the same quail embryo, (d)–(f) stages 13–15 from a different quail embryo, same orientation and location. The white arrows point to the location of possible tethers connecting the endocardium to the myocardium. Myo, myocardium; SV, sinus venosus; CJ, cardiac jelly; EC, endocardium; In, inflow; Out, outflow. (Courtesy of Andrew Rollins from Case Western University. Image reprinted from Jenkins et al. [120] with permission of OSA.)

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Fig. 22 Performance of 3D phase-resolved Doppler-FdOCT at different acquisition speeds covering a patch of 4°×4° across the optic nerve head. The volumes were recorded at line rates of 20kHz(A and J), 60kHz(D) and 100kHz(G). (A, D, G) Volumes containing phase-resolved Doppler-FdOCT tomograms in the RGB channel and intensity tomograms in the α-channel. (B, E, H) corresponding en-face cross-sections at significant positions. (C, F, I) corresponding fast axis cross-sections (B-scan) at significant positions. Solid arrows in (B, E, H) show vessels with lower flow speeds and almost perpendicular orientation to the detection axis. (Courtesy Rainer Letgeb from Medical University of Vienna, Image reprinted from Schmoll et al. [133] with permission of OSA.)

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Fig. 23 (a) Phase-resolved 4D velocity measurements using a retrospective gating procedure within the tadpole heart during the midsystolic phase of the cardiac cycle. (b) Single frame from the optical cardiogram gated structural movie at the level of spiral valve (SV) and atrio-ventricular valve (AVv) during peak systolic (a) and diastolic (b) phases of the cardiac cycle at 160ms and 775ms, respectively. (Courtesy of Alex Vitkin, Image reprinted from Mariampillai et al. [75], with permission of OSA.)

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Fig. 24 Phase-resolved swept source OCT velocity measurements from individual blood cells at 8.5dpc. (a) Structural and corresponding color-coded Doppler velocity images acquired at different phases of the heartbeat cycle. Green (online) corresponds to zero velocity. Individual blood cells are distinguishable in the dorsal aorta. (b) Average blood flow velocity as a function of time in the corresponding area of the dorsal aorta. (c) Blood flow velocity profiles at different phases of the cardiac cycle. Each data point corresponds to the Doppler OCT velocity measurement from an individual cell. The data points were regressed using a parabolic fit. (Courtesy of Kirill Larin from University of Houston, Image reprinted from Larina et al. [119], with permission of OSA.)

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Fig. 25 Illustration of the joint spectral and time-domain OCT (STdOCT) procedure.

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Fig. 26 Three-dimensional flow analysis in retinal and choroidal blood vessels performed by joint spectral and time-domain OCT (STdOCT); the white square indicates the analyzed region, C-choroidal blood vessels. En-face STdOCT velocity map shows spatial distribution of the axial component of measured velocity in three dimensions. Rapid changes between blue and red colors in vessels are caused by vessels orientation with respect to direction of sampling light beam.

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Fig. 27 (a) Dark-adapted and preadapted functional response for anesthetized Long–Evans rat’s retina. Data were obtained by averaging the photoreceptor outer segment reflectance from one volume acquired in 162ms. (b) Plot of the percent change in photoreceptor outer segment amplitude reflectance for t=2.6s compared with t=1.3s along with the cross-sectional data from one volume, which were unwrapped and flattened to the IS/OS boundary. (Image reprinted from Srinivasan et al. [164], with permission of OSA.)

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Fig. 28 (a), (b) High-quality SOCT cross-sectional retinal images of retina with multiple evanescent white dot syndrome (MEWDS) (a) obtained during the acute phase of the disease, revealing strong inhomogeneity on the reflectivity of a line corresponding to the inner/outer segments junction (IS/OS), and (b) measured after regaining visual acuity to 20/20. (c) Analysis of reflectivity for extracted retinal layers in respect to fluorescein angiography (FA). Strong reflectivity changes corresponding to hyperfluorescent spots in FA (exemplary indicated by arrows) are visible only in IS/OS layer. Reflectivity maps of RPE and choroid demonstrate homogenous distribution of backreflected light. The bright areas visible in the NFL map are specular reflections from the surface of the retina. The SOCT fundus view shows a superposition of all analyzed layers. Here the contrast of reflectivity changes in IS/OS layer is much smaller than in the separated IS/OS reflectivity map.

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Fig. 29 Reconstruction of spectral envelopes for flowing (blue curve online) versus stationary (red curve online) medium obtained by high-speed FdOCT imaging in retinal vessels in vivo: (a) Cross-sectional retinal image with Doppler signals indicating localization of blood vessels; rectangles correspond to the regions averaged to reconstruct the spectral envelopes. (b) Spectral envelope (darker curve) reconstructed from data corresponding to blood vessel (c) Spectral envelope (darker curve) reconstructed from data corresponding to static region of retina. Both curves are displayed along with the original spectrum emitted by an ASE light source (Broadlighter; gray curve).

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102. I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualising outer retinal pathology in non-exudative age- related macular degeneration,” Br. J. Ophthalmol. 93, 603–609 (2009).

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108. B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wcjtkowski, “Fuchs’ endothelial dystrophy in 830nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 39, S83–S85 (2008).

109. B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Fuchs’ endothelial dystrophy in 830nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 198–200 (2009).

110. V. Christopoulos, L. Kagemann, G. Wollstein, H. Ishikawa, M. L. Gabriele, M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, J. S. Duker, D. K. Dhaliwal, and J. S. Schuman, “In vivo corneal high-speed, ultra high-resolution optical coherence tomography,” Arch. Ophthalmol. 125, 1027–1035 (2007).

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115. D. C. Adler, C. Zhou, T. H. Tsai, J. Schmitt, Q. Huang, H. Mashimo, and J. G. Fujimoto, “Three-dimensional endomicroscopy of the human colon using optical coherence tomography,” Opt Express 17, 784–796 (2009).

116. D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photon. 1, 709–716 (2007). [CrossRef]  

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2009 (29)

I. Grulkowski, M. Gora, M. Szkulmowski, I. Gorczynska, D. Szlag, S. Marcos, A. Kowalczyk, and M. Wojtkowski, “Anterior segment imaging with spectral OCT system using a high-speed CMOS camera,” Opt. Express 17, 4842–4858 (2009).
[Crossref]

B. E. Bouma, S. H. Yun, B. J. Vakoc, M. J. Suter, and G. J. Tearney, “Fourier-domain optical coherence tomography: recent advances toward clinical utility,” Curr. Opin. Biotechnol. 20, 111–118 (2009).
[Crossref]

M. Gora, K. Karnowski, M. Szkulmowski, B. J. Kaluzny, R. Huber, A. Kowalczyk, and M. Wojtkowski, “Ultra high-speed swept source OCT imaging of the anterior segment of human eye at 200 kHz with adjustable imaging range,” Opt. Express 17, 14880–14894 (2009).
[Crossref]

B. Povazay, B. Hermann, B. Hofer, V. Kajic, E. Simpson, T. Bridgford, and W. Drexler, “Wide-field optical coherence tomography of the choroid in vivo,” Invest. Ophthalmol. Vis. Sci. 50, 1856–1863 (2009).

R. B. Rosen, M. Hathaway, J. Rogers, J. Pedro, P. Garcia, G. M. Dobre, and A. G. Podoleanu, “Simultaneous OCT/SLO/ICG imaging,” Invest. Ophthalmol. Vis. Sci. 50, 851–860(2009).

A. Szkulmowska, M. Szkulmowski, D. Szlag, A. Kowalczyk, and M. Wojtkowski, “Three-dimensional quantitative imaging of retinal and choroidal blood flow velocity using joint spectral and time-domain optical coherence tomography,” Opt Express 17, 10584–10598 (2009).

I. V. Larina, K. Furushima, M. E. Dickinson, R. R. Behringer, and K. V. Larin, “Live imaging of rat embryos with Doppler swept-source optical coherence tomography,” J. Biomed. Opt. 14, 050506 (2009).

B. R. Biedermann, W. Wieser, C. M. Eigenwillig, T. Klein, and R. Huber, “Dispersion, coherence and noise of Fourier-domain mode locked lasers,” Opt Express 17, 9947–9961 (2009).

M. Wojtkowski, B. Sikorski, I. Gorczynska, M. Gora, M. Szkulmowski, D. Bukowska, J. J. Kaluzny, J. G. Fujimoto, and A. Kowalczyk, “Comparison of reflectivity maps and outer retinal topography in retinal disease by three-dimensional Fourier-domain optical coherence tomography,” Opt. Express 17, 4189–4207 (2009).
[Crossref]

I. Gorczynska, V. J. Srinivasan, L. N. Vuong, R. W. Chen, J. J. Liu, E. Reichel, M. Wojtkowski, J. S. Schuman, J. S. Duker, and J. G. Fujimoto, “Projection OCT fundus imaging for visualising outer retinal pathology in non-exudative age-related macular degeneration,” Br. J. Ophthalmol. 93, 603–609 (2009).

J. J. Kaluzny, M. Wojtkowski, B. L. Sikorski, M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, J. G. Fujimoto, J. S. Duker, J. S. Schuman, and A. Kowalczyk, “Analysis of the outer retina reconstructed by high-resolution, three-dimensional spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 102–108 (2009).

T. Fabritius, S. Makita, M. Miura, R. Myllyla, and Y. Yasuno, “Automated segmentation of the macula by optical coherence tomography,” Opt Express 17, 15659–15669 (2009).

B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Fuchs’ endothelial dystrophy in 830 nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 198–200 (2009).

D. C. Adler, C. Zhou, T. H. Tsai, J. Schmitt, Q. Huang, H. Mashimo, and J. G. Fujimoto, “Three-dimensional endomicroscopy of the human colon using optical coherence tomography,” Opt Express 17, 784–796 (2009).

I. V. Larina, S. Ivers, S. Syed, M. E. Dickinson, and K. V. Larin, “Hemodynamic measurements from individual blood cells in early mammalian embryos with Doppler swept source OCT,” Opt. Lett. 34, 986–988 (2009).
[Crossref]

B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15, 1219–1223 (2009).

T. Schmoll, C. Kolbitsch, and R. A. Leitgeb, “Ultra-high-speed volumetric tomography of human retinal blood flow,” Opt Express 17, 4166–4176 (2009).

Y. Jia, P. O. Bagnaninchi, Y. Yang, A. E. Haj, M. T. Hinds, S. J. Kirkpatrick, and R. K. Wang, “Doppler optical coherence tomography imaging of local fluid flow and shear stress within microporous scaffolds,” J. Biomed. Opt. 14, 034014 (2009).

R. K. Wang and L. An, “Doppler optical micro-angiography for volumetric imaging of vascular perfusion in vivo,” Opt. Express 17, 8926–8940 (2009).
[Crossref]

Y. K. Tao, K. M. Kennedy, and J. A. Izatt, “Velocity-resolved three-dimensional retinal microvessel imaging using single-pass flow imaging spectral domain optical coherence tomography,” Opt. Express 17, 4177–4188 (2009).
[Crossref]

M. Szkulmowski, I. Grulkowski, D. Szlag, A. Szkulmowska, A. Kowalczyk, and M. Wojtkowski, “Flow velocity estimation by complex ambiguity free joint spectral and time-domain optical coherence tomography,” Opt. Express 17, 14281–14297 (2009).
[Crossref]

K. Tsunoda, G. Hanazono, K. Inomata, Y. Kazato, W. Suzuki, and M. Tanifuji, “Origins of retinal intrinsic signals: a series of experiments on retinas of macaque monkeys,” Jpn. J. Ophthalmol. 53, 297–314 (2009).

V. J. Srinivasan, Y. Chen, J. S. Duker, and J. G. Fujimoto, “In vivo functional imaging of intrinsic scattering changes in the human retina with high-speed ultrahigh resolution OCT,” Opt. Express 17, 3861–3877 (2009).
[Crossref]

A. R. Tumlinson, B. Hermann, B. Hofer, B. Povazay, T. H. Margrain, A. M. Binns, and W. Drexler, “Techniques for extraction of depth-resolved in vivo human retinal intrinsic optical signals with optical coherence tomography,” Jpn. J. Ophthalmol. 53, 315–326 (2009).

C. Ahlers, E. Goetzinger, M. Pircher, I. Golbaz, F. Prager, C. Schutze, B. Baumann, C. Hitzenberger, and U. Schmidt-Erfurth, “Imaging of the retinal pigment epithelium in age-related macular degeneration using polarization sensitive optical coherence tomography,” Investig. Ophthalmol. Vis. Sci. doi:10.1167/iovs.09-3817 (2009).

E. Gotzinger, M. Pircher, B. Baumann, C. Ahlers, W. Geitzenauer, U. Schmidt-Erfurth, and C. K. Hitzenberger, “Three-dimensional polarization sensitive OCT imaging and interactive display of the human retina,” Opt. Express 17, 4151–4165 (2009).
[Crossref]

M. Yamanari, Y. Lim, S. Makita, and Y. Yasuno, “Visualization of phase retardation of deep posterior eye by polarization-sensitive swept-source optical coherence tomography with 1 μm probe,” Opt. Express 17, 12385–12396(2009).
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S. Kray, F. Spoler, M. Forst, and H. Kurz, “High-resolution simultaneous dual-band spectral domain optical coherence tomography,” Opt. Lett. 34, 1970–1972 (2009).
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S. Tamborski, D. Bukowska, M. Szkulmowski, A. Szkulmowska, A. Kowalczyk, and M. Wojtkowski, “Simultaneous analysis of flow velocity and spectroscopic properties of scattering media with the use of joint spectral and time-domain OCT,” Photon. Lett. Poland 1, 49–51 (2009).

2008 (26)

E. Goetzinger, M. Pircher, W. Geitzenauer, C. Ahlers, B. Baumann, S. Michels, U. Schmidt-Erfurth, and C. K. Hitzenberger, “Retinal pigment epithelium segmentation by polarization sensitive optical coherence tomography,” Opt. Express 16, 16410–16422 (2008).
[Crossref]

P. Targowski, B. Rouba, M. Góra, L. Tymińska-Widmer, J. Marczak, and A. Kowalczyk, “Optical coherence tomography in art diagnostic and restoration,” Appl. Phys. A 92, 1–9 (2008).
[Crossref]

X. Liang, A. L. Oldenburg, V. Crecea, E. J. Chaney, and S. A. Boppart, “Optical micro-scale mapping of dynamic biomechanical tissue properties,” Opt. Express 16, 11052–11065 (2008).
[Crossref]

M. Miura, M. Yamanari, T. Iwasaki, A. E. Elsner, S. Makita, T. Yatagai, and Y. Yasuno, “Imaging polarimetry in age-related macular degeneration,” Investig. Ophthalmol. Vis. Sci. 49, 2661–2667 (2008).

M. Yamanari, S. Makita, and Y. Yasuno, “Polarization-sensitive swept-source optical coherence tomography with continuous source polarization modulation,” Opt. Express 16, 5892–5906 (2008).
[Crossref]

K. Grieve and A. Roorda, “Intrinsic signals from human cone photoreceptors,” Investig. Ophthalmol. Vis. Sci. 49, 713–719(2008).

G. Hanazono, K. Tsunoda, Y. Kazato, K. Tsubota, and M. Tanifuji, “Evaluating neural activity of retinal ganglion cells by flash-evoked intrinsic signal imaging in macaque retina,” Investig. Ophthalmol. Vis. Sci. 49, 4655–4663 (2008).

L. An and R. K. Wang, “In vivo volumetric imaging of vascular perfusion within human retina and choroids with optical micro-angiography,” Opt. Express 16, 11438–11452 (2008).
[Crossref]

S. Makita, T. Fabritius, and Y. Yasuno, “Quantitative retinal-blood flow measurement with three-dimensional vessel geometry determination using ultrahigh-resolution Doppler optical coherence angiography,” Opt. Lett. 33, 836–838(2008).
[Crossref]

M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Flow velocity estimation using joint spectral and time-domain optical coherence tomography,” Opt. Express 16, 6008–6025 (2008).
[Crossref]

A. Szkulmowska, M. Szkulmowski, A. Kowalczyk, and M. Wojtkowski, “Phase-resolved Doppler optical coherence tomography—limitations and improvements,” Opt. Lett. 33, 1425–1427 (2008).
[Crossref]

B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wcjtkowski, “Fuchs’ endothelial dystrophy in 830 nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 39, S83–S85 (2008).

I. V. Larina, N. Sudheendran, M. Ghosn, J. Jiang, A. Cable, K. V. Larin, and M. E. Dickinson, “Live imaging of blood flow in mammalian embryos using Doppler swept-source optical coherence tomography,” J. Biomed. Opt. 13, 060506(2008).

M. V. Sarunic, S. Asrani, and J. A. Izatt, “Imaging the ocular anterior segment with real-time, full-range Fourier-domain optical coherence tomography,” Arch. Ophthalmol. 126, 537–542 (2008).

L. Plesea and A. G. Podoleanu, “Direct corneal elevation measurements using multiple delay en face optical coherence tomography,” J. Biomed. Opt. 13, 054054 (2008).

A. C. Cheng, S. K. Rao, S. Lau, C. K. Leung, and D. S. Lam, “Central corneal thickness measurements by ultrasound, Orbscan II, and Visante OCT after LASIK for myopia,” J. Refract. Surg. 24, 361–365 (2008).

B. L. Sikorski, M. Wojtkowski, J. J. Kaluzny, M. Szkulmowski, and A. Kowalczyk, “Correlation of spectral optical coherence tomography with fluorescein and indocyanine green angiography in multiple evanescent white dot syndrome,” Br. J. Ophthalmol. 92, 1552–1557 (2008).
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D. Choi, H. Hiro-Oka, H. Furukawa, R. Yoshimura, M. Nakanishi, K. Shimizu, and K. Ohbayashi, “Fourier-domain optical coherence tomography using optical demultiplexers imaging at 60,000,000 lines/s,” Opt. Lett. 33, 1318–1320(2008).
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C. M. Eigenwillig, B. R. Biedermann, G. Palte, and R. Huber, “K-space linear Fourier-domain mode locked laser and applications for optical coherence tomography,” Opt. Express 16, 8916–8937 (2008).
[Crossref]

B. R. Biedermann, W. Wieser, C. M. Eigenwillig, G. Palte, D. C. Adler, V. J. Srinivasan, J. G. Fujimoto, and R. Huber, “Real time en face Fourier-domain optical coherence tomography with direct hardware frequency demodulation,” Opt. Lett. 33, 2556–2558 (2008).
[Crossref]

T. Bajraszewski, M. Wojtkowski, M. Szkulmowski, A. Szkulmowska, R. Huber, and A. Kowalczyk, “Improved spectral optical coherence tomography using optical frequency comb,” Opt. Express 16, 4163–4176 (2008).
[Crossref]

A. Dubois, J. Moreau, and C. Boccara, “Spectroscopic ultrahigh-resolution full-field optical coherence microscopy,” Opt. Express 16, 17082–17091 (2008).
[Crossref]

S. Makita, T. Fabritius, and Y. Yasuno, “Full-range, high-speed, high-resolution 1 μm spectral-domain optical coherence tomography using BM-scan for volumetric imaging of the human posterior eye,” Opt. Express 16, 8406–8420(2008).
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M. Miura, K. Kawana, T. Iwasaki, T. Kiuchi, T. Oshika, H. Mori, M. Yamanari, S. Makita, T. Yatagai, and Y. Yasuno, “Three-dimensional anterior segment optical coherence tomography of filtering blebs after trabeculectomy,” J. Glaucoma 17, 193–196 (2008).

G. J. Tearney, S. Waxman, M. Shishkov, B. J. Vakoc, M. J. Suter, M. I. Freilich, A. E. Desjardins, W. Y. Oh, L. A. Bartlett, M. Rosenberg, and B. E. Bouma, “Three-dimensional coronary artery microscopy by intracoronary optical frequency domain imaging,” JACC Cardiovasc. Imaging 1, 752–761 (2008).

B. Potsaid, I. Gorczynska, V. J. Srinivasan, Y. Chen, J. Jiang, A. Cable, and J. G. Fujimoto, “Ultrahigh speed spectral / Fourier-domain OCT ophthalmic imaging at 70,000 to 312,500 A-scans/s,” Opt. Express 16, 15149–15169 (2008).
[Crossref]

2007 (18)

S. W. Huang, A. D. Aguirre, R. A. Huber, D. C. Adler, and J. G. Fujimoto, “Swept source optical coherence microscopy using a Fourier-domain mode-locked laser,” Opt. Express 15, 6210–6217 (2007).
[Crossref]

R. Huber, D. C. Adler, V. J. Srinivasan, and J. G. Fujimoto, “Fourier-domain mode locking at 1050 nm for ultrahigh-speed optical coherence tomography of the human retina at 236,000 axial scans per second,” Opt. Lett. 32, 2049–2051 (2007).
[Crossref]

T. Bajraszewski, M. Wojtkowski, A. Szkulmowska, W. Fojt, M. Szkulmowski, and A. Kowalczyk, “Fourier-domain optical coherence tomography using optical frequency comb,” Proc. SPIE 6429, 64291F (2007).

S. W. Huang, A. D. Aguirre, R. A. Huber, D. C. Adler, and J. G. Fujimoto, “Swept source optical coherence microscopy using a Fourier-domain mode-locked laser,” Opt Express 15, 6210–6217 (2007).

A. Mariampillai, B. A. Standish, N. R. Munce, C. Randall, G. Liu, J. Y. Jiang, A. E. Cable, I. A. Vitkin, and V. X. D. Yang, “Doppler optical cardiogram gated 2D color flow imaging at 1000 fps and 4D in vivo visualization of embryonic heart at 45 fps on a swept source OCT system,” Opt. Express 15, 1627–1638 (2007).
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R. J. Zawadzki, A. R. Fuller, D. F. Wiley, B. Hamann, S. S. Choi, and J. S. Werner, “Adaptation of a support vector machine algorithm for segmentation and visualization of retinal structures in volumetric optical coherence tomography data sets,” J. Biomed. Opt. 12, 041206 (2007).

B. J. Kaluzny, W. Fojt, A. Szkulmowska, T. Bajraszewski, M. Wojtkowski, and A. Kowalczyk, “Spectral optical coherence tomography in video-rate and three-dimensional imaging of contact lens wear,” Optom. Vis. Sci. 84, 1104–1109 (2007).

V. Christopoulos, L. Kagemann, G. Wollstein, H. Ishikawa, M. L. Gabriele, M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, J. S. Duker, D. K. Dhaliwal, and J. S. Schuman, “In vivo corneal high-speed, ultra high-resolution optical coherence tomography,” Arch. Ophthalmol. 125, 1027–1035 (2007).

D. C. Adler, Y. Chen, R. Huber, J. Schmitt, J. Connolly, and J. G. Fujimoto, “Three-dimensional endomicroscopy using optical coherence tomography,” Nat. Photon. 1, 709–716 (2007).
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B. J. Vakoc, M. Shishko, S. H. Yun, W. Y. Oh, M. J. Suter, A. E. Desjardins, J. A. Evans, N. S. Nishioka, G. J. Tearney, and B. E. Bouma, “Comprehensive esophageal microscopy by using optical frequency-domain imaging (with video),” Gastroint. Endosc. 65, 898–905 (2007).
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M. W. Jenkins, D. C. Adler, M. Gargesha, R. Huber, F. Rothenberg, J. Belding, M. Watanabe, D. L. Wilson, J. G. Fujimoto, and A. M. Rollins, “Ultrahigh-speed optical coherence tomography imaging and visualization of the embryonic avian heart using a buffered Fourier domain mode locked laser,” Opt. Express 15, 6251–6267 (2007).
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M. W. Jenkins, O. Q. Chughtai, A. N. Basavanhally, M. Watanabe, and A. M. Rollins, “In vivo gated 4D imaging of the embryonic heart using optical coherence tomography,” J. Biomed. Opt. 12, 030505 (2007).

T. Akkin, C. Joo, and J. F. de Boer, “Depth-resolved measurement of transient structural changes during action potential propagation,” Biophys. J. 93, 1347–1353 (2007).
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A. H. Bachmann, M. L. Villiger, C. Blatter, T. Lasser, and R. A. Leitgeb, “Resonant Doppler flow imaging and optical vivisection of retinal blood vessels,” Opt. Express 15, 408–422 (2007).
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Y. K. Tao, M. Zhao, and J. A. Izatt, “High-speed complex conjugate resolved retinal spectral domain optical coherence tomography using sinusoidal phase modulation,” Opt. Lett. 32, 2918–2920 (2007).
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G. Hanazono, K. Tsunoda, K. Shinoda, K. Tsubota, Y. Miyake, and M. Tanifuji, “Intrinsic signal imaging in macaque retina reveals different types of flash-induced light reflectance changes of different origins,” Investig. Ophthalmol. Vis. Sci. 48, 2903–2912 (2007).

R. S. Jonnal, J. Rha, Y. Zhang, B. Cense, W. Gao, and D. T. Miller, “In vivo functional imaging of human cone photoreceptors,” Opt. Express 15, 16141–16160 (2007).
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A. M. Zysk, F. T. Nguyen, A. L. Oldenburg, D. L. Marks, and S. A. Boppart, “Optical coherence tomography: a review of clinical development from bench to bedside,” J Biomed Opt 12, 051403 (2007).

2006 (19)

A. L. Oldenburg, M. N. Hansen, D. A. Zweifel, A. Wei, and S. A. Boppart, “Plasmon-resonant gold nanorods as low backscattering albedo contrast agents for optical coherence tomography,” Opt. Express 14, 6724–6738 (2006).
[Crossref]

W. Tan, A. L. Oldenburg, J. J. Norman, T. A. Desai, and S. A. Boppart, “Optical coherence tomography of cell dynamics in three-dimensional tissue models,” Opt. Express 14, 7159–7171 (2006).
[Crossref]

B. E. Applegate and J. A. Izatt, “Molecular imaging of endogenous and exogenous chromophores using ground state recovery pump-probe optical coherence tomography,” Opt. Express 14, 9142–9155 (2006).
[Crossref]

K. Bizheva, R. Pflug, B. Hermann, B. Povazay, H. Sattmann, P. Qiu, E. Anger, H. Reitsamer, S. Popov, J. R. Taylor, A. Unterhuber, P. Ahnelt, and W. Drexler, “Optophysiology: depth-resolved probing of retinal physiology with functional ultrahigh-resolution optical coherence tomography,” Proc. Natl. Acad. Sci. U.S.A. 103, 5066–5071 (2006).

V. J. Srinivasan, M. Wojtkowski, J. G. Fujimoto, and J. S. Duker, “In vivo measurement of retinal physiology with high-speed ultrahigh-resolution optical coherence tomography,” Opt. Lett. 31, 2308–2310 (2006).
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M. D. Abramoff, Y. H. Kwon, D. Ts’o, P. Soliz, B. Zimmerman, J. Pokorny, and R. Kardon, “Visual stimulus-induced changes in human near-infrared fundus reflectance,” Investig. Ophthalmic Vis Sci. 47, 715–721. (2006).

Y. Yasuno, S. Makita, T. Endo, G. Aoki, M. Itoh, and T. Yatagai, “Simultaneous B-M-mode scanning method for real-time full-range Fourier-domain optical coherence tomography,” Appl. Opt. 45, 1861–1865 (2006).
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S. Makita, Y. Hong, M. Yamanari, T. Yatagai, and Y. Yasuno, “Optical coherence angiography,” Opt. Express 14, 7821–7840 (2006).
[Crossref]

R. Navarro, L. Gonzalez, and J. L. Hernandez, “Optics of the average normal cornea from general and canonical representations of its surface topography,” J. Opt. Soc. Am. A 23, 219–232 (2006).
[Crossref]

B. J. Kaluzny, J. J. Kaluzny, A. Szkulmowska, I. Gorczynska, M. Szkulmowski, T. Bajraszewski, M. Wojtkowski, and P. Targowski, “Spectral optical coherence tomography: a novel technique for cornea imaging,” Cornea 25, 960–965 (2006).
[Crossref]

V. J. Srinivasan, M. Wojtkowski, A. J. Witkin, J. S. Duker, T. H. Ko, M. Carvalho, J. S. Schuman, A. Kowalczyk, and J. G. Fujimoto, “High-definition and 3-dimensional imaging of macular pathologies with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology annual 113, 2054–2065 (2006).
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R. A. Costa, M. Skaf, L. A. Melo, Jr., D. Calucci, J. A. Cardillo, J. C. Castro, D. Huang, and M. Wojtkowski, “Retinal assessment using optical coherence tomography,” Prog. Retin. Eye Res. 25, 325–353 (2006).

W. Y. Oh, B. E. Bouma, N. Iftimia, S. H. Yun, R. Yelin, and G. J. Tearney, “Ultrahigh-resolution full-field optical coherence microscopy using InGaAs camera,” Opt. Express 14, 726–735(2006).
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S. Moon and D. Y. Kim, “Ultra-high-speed optical coherence tomography with a stretched pulse supercontinuum source,” Opt. Express 14, 11575–11584 (2006).
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J. Zhang, Q. Wang, B. Rao, Z. P. Chen, and K. Hsu, “Swept laser source at 1 μm for Fourier-domain optical coherence tomography,” Appl. Phys. Lett. 89, 073901 (2006).
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R. Huber, M. Wojtkowski, and J. G. Fujimoto, “Fourier domain mode locking (FDML): a new laser operating regime and applications for optical coherence tomography,” Opt. Express 14, 3225–3237 (2006).
[Crossref]

R. Huber, D. C. Adler, and J. G. Fujimoto, “Buffered Fourier-domain mode locking: unidirectional swept laser sources for optical coherence tomography imaging at 370,000 lines/s,” Opt. Lett. 31, 2975–2977 (2006).
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W. Y. Oh, S. H. Yun, B. J. Vakoc, G. J. Tearney, and B. E. Bouma, “Ultrahigh-speed optical frequency domain imaging and application to laser ablation monitoring,” Appl. Phys. Lett. 88, (2006).

M. V. Sarunic, S. Weinberg, and J. A. Izatt, “Full-field swept-source phase microscopy,” Opt. Lett. 31, 1462–1464(2006).
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2005 (15)

A. Unterhuber, B. Povazay, B. Hermann, H. Sattmann, A. Chavez-Pirson, and W. Drexler, “In vivo retinal optical coherence tomography at 1040 nm-enhanced penetration into the choroid,” Opt. Express 13, 3252–3258 (2005).
[Crossref]

K. Grieve, G. Moneron, A. Dubois, J.-F. Le Gargasson, and C. Boccara, “Ultrahigh resolution ex vivo ocular imaging using ultrashort acquisition time en face optical coherence tomography,” J. Opt. A Pure Appl. Opt. 7, 368–373 (2005).
[Crossref]

G. M. Dobre, A. G. Podoleanu, and R. B. Rosen, “Simultaneous optical coherence tomography—Indocyanine Green dye fluorescence imaging system for investigations of the eye’s fundus,” Opt. Lett. 30, 58–60 (2005).
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W. Y. Oh, S. H. Yun, G. J. Tearney, and B. E. Bouma, “115 kHz tuning repetition rate ultrahigh-speed wavelength-swept semiconductor laser,” Opt. Lett. 30, 3159–3161 (2005).
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M. A. Choma, K. Hsu, and J. A. Izatt, “Swept source optical coherence tomography using an all-fiber 1300 nm ring laser source,” J. Biomed. Opt. 10, 044009 (2005).

R. Huber, M. Wojtkowski, J. G. Fujimoto, J. Y. Jiang, and A. E. Cable, “Three-dimensional and C-mode OCT imaging with a compact, frequency swept laser source at 1300 nm,” Opt. Express 13, 10523–10538 (2005).
[Crossref]

R. Huber, M. Wojtkowski, K. Taira, J. Fujimoto, and K. Hsu, “Amplified, frequency swept lasers for frequency domain reflectometry and OCT imaging: design and scaling principles,” Opt. Express 13, 3513–3528 (2005).
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M. Wojtkowski, V. Srinivasan, J. G. Fujimoto, T. Ko, J. S. Schuman, A. Kowalczyk, and J. S. Duker, “Three-dimensional retinal imaging with high-speed ultrahigh-resolution optical coherence tomography,” Ophthalmology annual 112, 1734–1746 (2005).
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A. Szkulmowska, M. Wojtkowski, I. Gorczynska, T. Bajraszewski, M. Szkulmowski, P. Targowski, A. Kowalczyk, and J. J. Kaluzny, “Coherent noise-free ophthalmic imaging by spectral optical coherence tomography,” J. Phys. D 38, 2606–2611 (2005).
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B. Grajciar, M. Pircher, A. Fercher, and R. Leitgeb, “Parallel Fourier-domain optical coherence tomography for in vivo measurement of the human eye,” Opt. Express 13, 1131–1137(2005).
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S. L. Jiao, R. Knighton, X. R. Huang, G. Gregori, and C. A. Puliafito, “Simultaneous acquisition of sectional and fundus ophthalmic images with spectral-domain optical coherence tomography,” Opt. Express 13, 444–452 (2005).
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D. A. Nelson, S. Krupsky, A. Pollack, E. Aloni, M. Belkin, I. Vanzetta, M. Rosner, and A. Grinvald, “Special report: Noninvasive multi-parameter functional optical imaging of the eye,” Ophthalmic Surg. Lasers Imaging 36, 57–66(2005).

M. V. Sarunic, B. E. Applegate, and J. A. Izatt, “Spectral domain second-harmonic optical coherence tomography,” Opt. Lett. 30, 2391–2393 (2005).
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Y. Jiang, I. V. Tomov, Y. Wang, and Z. Chen, “High-resolution second-harmonic optical coherence tomography of collagen in rat-tail tendon,” Appl. Phys. Lett. 86, 133901–133901(2005).
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M. A. Choma, A. K. Ellerbee, C. Yang, T. L. Creazzo, and J. A. Izatt, “Spectral-domain phase microscopy,” Opt. Lett. 30, 1162–1164 (2005).
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2004 (15)

P. Targowski, B. Rouba, M. Wojtkowski, and A. Kowalczyk, “The application of optical coherence tomography to non-destructive examination of museum objects,” Stud. Conserv. 49, 107–114 (2004).

K. Tsunoda, Y. Oguchi, G. Hanazono, and M. Tanifuji, “Mapping cone- and rod-induced retinal responsiveness in macaque retina by optical imaging,” Investig. Ophthalmol. Vis.. Sci. 45, 3820–3826 (2004).

D. J. Faber, F. J. van der Meer, and M. C. G. Aalders, “Quantitative measurement of attenuation coefficients of weakly scattering media using optical coherence tomography,” Opt. Express 12, 4353–4365 (2004).
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B. Hermann, K. Bizheva, A. Unterhuber, B. Povazay, H. Sattmann, L. Schmetterer, A. F. Fercher, and W. Drexler, “Precision of extracting absorption profiles from weakly scattering media with spectroscopic time-domain optical coherence tomography,” Opt. Express 12, 1677–1688 (2004).
[Crossref]

R. A. Leitgeb, W. Drexler, A. Unterhuber, B. Hermann, T. Bajraszewski, T. Le, A. Stingl, and A. F. Fercher, “Ultrahigh resolution Fourier-domain optical coherence tomography,” Opt. Express 12, 2156–2165 (2004).
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P. Koch, G. Huttmann, H. Schleiermacher, J. Eichholz, and E. Koch, “Linear optical coherence tomography system with a downconverted fringe pattern,” Opt. Lett. 29, 1644–1646(2004).
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S. H. Yun, G. J. Tearney, J. F. de Boer, and B. E. Bouma, “Motion artifacts in optical coherence tomography with frequency-domain ranging,” Opt. Express 12, 2977–2998 (2004).
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T. Akkin, D. P. Dave, T. E. Milner, and H. G. Rylander, “Detection of neural activity using phase-sensitive optical low-coherence reflectometry,” Opt. Express 12, 2377–2386(2004).
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C. Fang-Yen, M. C. Chu, H. S. Seung, R. R. Dasari, and M. S. Feld, “Noncontact measurement of nerve displacement during action potential with a dual-beam low-coherence interferometer,” Opt. Lett. 29, 2028–2030 (2004).
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N. Nassif, B. Cense, B. H. Park, S. H. Yun, T. C. Chen, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “In vivo human retinal imaging by ultrahigh-speed spectral domain optical coherence tomography,” Opt. Lett. 29, 480–482 (2004).
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B. Cense, N. A. Nassif, T. C. Chen, M. C. Pierce, S.-H. Yun, B. H. Park, B. E. Bouma, G. J. Tearney, and J. F. de Boer, “Ultrahigh-resolution high-speed retinal imaging using spectral-domain optical coherence tomography,” Opt. Express 12, 2435–2447 (2004).
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M. Wojtkowski, V. J. Srinivasan, T. H. Ko, J. G. Fujimoto, A. Kowalczyk, and J. S. Duker, “Ultrahigh-resolution high-speed Fourier-domain optical coherence tomography and methods for dispersion compensation,” Opt. Express 12, 2404–2422 (2004).
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N. A. Nassif, B. Cense, B. H. Park, M. C. Pierce, S. H. Yun, B. E. Bouma, G. J. Tearney, T. C. Chen, and J. F. de Boer, “In vivo high-resolution video-rate spectral-domain optical coherence tomography of the human retina and optic nerve,” Opt. Express 12, 367–376 (2004).
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M. Wojtkowski, T. Bajraszewski, I. Gorczynska, P. Targowski, A. Kowalczyk, W. Wasilewski, and C. Radzewicz, “Ophthalmic imaging by spectral optical coherence tomography,” Am. J. Ophthalmol. 138, 412–419 (2004).
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A. Dubois, K. Grieve, G. Moneron, R. Lecaque, L. Vabre, and C. Boccara, “Ultrahigh-resolution full-field optical coherence tomography,” Appl. Opt. 43, 2874–2883 (2004).
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2003 (18)

B. Povazay, K. Bizheva, B. Hermann, A. Unterhuber, H. Sattmann, A. F. Fercher, W. Drexler, C. Schubert, P. K. Ahnelt, M. Mei, R. Holzwarth, W. J. Wadsworth, J. C. Knight, and P. S. Russel, “Enhanced visualization of choroidal vessels using ultrahigh resolution ophthalmic OCT at 1050 nm,” Opt. Express 11, 1980–1986 (2003).

S. Yun, G. Tearney, J. de Boer, N. Iftimia, and B. Bouma, “High-speed optical frequency-domain imaging,” Opt. Express 11, 2953–2963 (2003).
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S. H. Yun, C. Boudoux, G. J. Tearney, and B. E. Bouma, “High-speed wavelength-swept semiconductor laser with a polygon-scanner-based wavelength filter,” Opt. Lett. 28, 1981–1983 (2003).
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M. Wojtkowski, T. Bajraszewski, P. Targowski, and A. Kowalczyk, “Real-time in vivo imaging by high-speed spectral optical coherence tomography,” Opt. Lett. 28, 1745–1747(2003).
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S. H. Yun, G. J. Tearney, B. E. Bouma, B. H. Park, and J. F. de Boer, “High-speed spectral-domain optical coherence tomography at 1.3 μm wavelength,” Opt. Express 11, 2953–2963 (2003).
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A. F. Fercher, W. Drexler, C. K. Hitzenberger, and T. Lasser, “Optical coherence tomography-principles and applications,” Rep. Prog. Phys. 66, 239–303 (2003).
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C. K. Hitzenberger, P. Trost, P. W. Lo, and Q. Y. Zhou, “Three-dimensional imaging of the human retina by high-speed optical coherence tomography,” Opt. Express 11, 2753–2761(2003).

M. Akiba, K. P. Chan, and N. Tanno, “Full-field optical coherence tomography by 2D heterodyne detection with a pair of CCD cameras,” Opt. Lett. 28, 816–818 (2003).
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R. Leitgeb, C. K. Hitzenberger, and A. F. Fercher, “Performance of Fourier-domain vs. time domain optical coherence tomography,” Opt. Express 11, 889–894 (2003).

M. A. Choma, M. V. Sarunic, C. H. Yang, and J. A. Izatt, “Sensitivity advantage of swept source and Fourier-domain optical coherence tomography,” Opt. Express 11, 2183–2189(2003).

J. F. de Boer, B. Cense, B. H. Park, M. C. Pierce, G. J. Tearney, and B. E. Bouma, “Improved signal-to-noise ratio in spectral-domain compared with time-domain optical coherence tomography,” Opt. Lett. 28, 2067–2069 (2003).
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M. Lazebnik, D. L. Marks, K. Potgieter, R. Gillette, and S. A. Boppart, “Functional optical coherence tomography for detecting neural activity through scattering changes,” Opt. Lett. 28, 1218–1220 (2003).
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R. A. Leitgeb, L. Schmetterer, W. Drexler, A. F. Fercher, R. J. Zawadzki, and T. Bajraszewski, “Real-time assessment of retinal blood flow with ultrafast acquisition by color Doppler Fourier-domain optical coherence tomography,” Opt. Express 11, 3116–3121 (2003).

B. H. Park, M. C. Pierce, B. Cense, and J. F. de Boer, “Real-time multi-functional optical coherence tomography,” Opt. Express 11, 782–793 (2003).
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B. R. White, M. C. Pierce, N. Nassif, B. Cense, B. H. Park, G. J. Tearney, B. E. Bouma, T. C. Chen, and J. F. de Boer, “In vivo dynamic human retinal blood flow imaging using ultrahigh-speed spectral domain optical Doppler tomography,” Opt. Express 11, 3490–3497 (2003).

D. L. Faber, E. G. Mik, M. C. G. Aalders, and T. G. van Leeuwen, “Light absorption of (oxy-)hemoglobin assessed by spectroscopic optical coherence tomography,” Opt. Lett. 28, 1436–1438 (2003).
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D. Stifter, P. Burgholzer, O. Hoglinger, E. Gotzinger, and C. K. Hitzenberger, “Polarisation-sensitive optical coherence tomography for material characterisation and strain-field mapping,” Appl. Phys. A 76, 947–951 (2003).
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2002 (4)

R. U. Maheswari, H. Takaoka, R. Homma, H. Kadono, and M. Tanifuji, “Implementation of optical coherence tomography (OCT) in visualization of functional structures of cat visual cortex,” Opt. Commun. 202, 47–54 (2002).
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S. Sanders, D. Mattison, L. Ma, J. Jeffries, and R. Hanson, “Wavelength-agile diode-laser sensing strategies for monitoring gas properties in optically harsh flows: application in cesium-seeded pulse detonation,” Opt. Express 10, 505–514(2002).

M. Wojtkowski, R. Leitgeb, A. Kowalczyk, T. Bajraszewski, and A. F. Fercher, “In vivo human retinal imaging by Fourier-domain optical coherence tomography,” J. Biomed. Opt. 7, 457–463 (2002).

M. Wojtkowski, A. Kowalczyk, R. Leitgeb, and A. F. Fercher, “Full range complex spectral optical coherence tomography technique in eye imaging,” Opt. Lett. 27, 1415–1417 (2002).
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2000 (6)

1999 (2)

1998 (6)

1997 (11)

Z. Chen, T. E. Milner, S. Srinivas, X. Wang, A. Malekafzali, M. J. C. van Gemert, and J. S. Nelson, “Noninvasive imaging of in vivo blood flow velocity using optical Doppler tomography,” Opt. Lett. 22, 1119–1121 (1997).
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J. A. Izatt, M. D. Kulkami, S. Yazdanfar, J. K. Barton, and A. J. Welch, “In vivo bidirectional color Doppler flow imaging of picoliter blood volumes using optical coherence tomography,” Opt. Lett. 22, 1439–1441 (1997).
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S. Yazdanfar, M. D. Kulkarni, and J. A. Izatt, “High resolution imaging of in vivo cardiac dynamics using color Doppler optical coherence tomography,” Opt. Express 1, 424–431(1997).
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A. Villringer and B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
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X. Wang, T. E. Milner, Z. Chen, and J. S. Nelson, “Measurement of fluid-flow-velocity profile in turbid media by the use of optical Doppler tomography,” Appl Optics 36, 144–149(1997).

S. R. Chinn, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography using a frequency-tunable optical source,” Opt. Lett. 22, 340–342 (1997).
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F. Lexer, C. K. Hitzenberger, A. F. Fercher, and M. Kulhavy, “Wavelength-tuning interferometry of intraocular distances,” Appl. Opt. 36, 6548–6553 (1997).
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G. J. Tearney, M. E. Brezinski, B. E. Bouma, S. A. Boppart, C. Pitvis, J. F. Southern, and J. G. Fujimoto, “In vivo endoscopic optical biopsy with optical coherence tomography,” Science 276, 2037–2039 (1997).
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G. J. Tearney, B. E. Bouma, and J. G. Fujimoto, “High-speed phase- and group-delay scanning with a grating-based phase control delay line,” Opt. Lett. 22, 1811–1813 (1997).
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B. Golubovic, B. Bouma, G. Tearney, and J. Fujimoto, “Optical frequency-domain reflectometry using rapid wavelength tuning of a Cr4+ forsterite laser,” Opt. Lett. 22, 1704–1706 (1997).
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1996 (4)

G. J. Tearney, B. E. Bouma, S. A. Boppart, B. Golubovic, E. A. Swanson, and J. G. Fujimoto, “Rapid acquisition of in vivo biological images by use of optical coherence tomography,” Opt. Lett. 21, 1408–1410 (1996).
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A. Fercher, “Optical coherence tomography,” J. Biomed. Opt. 1, 157–173 (1996).

M. R. Hee, C. R. Baumal, C. A. Puliafito, J. S. Duker, E. Reichel, J. R. Wilkins, J. G. Coker, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of age-related macular degeneration and choroidal neovascularization,” Ophthalmology annual 103, 1260–1270 (1996).

J. S. Schuman, T. PedutKloizman, L. Pieroth, E. Hertzmark, M. R. Hee, J. R. Wilkins, J. G. Coker, C. A. Puliafito, J. G. Fujimoto, and E. A. Swanson, “Quantitation of nerve fiber layer thickness loss over time in the glaucomatous monkey model using optical coherence tomography,” Investig. Ophthal. Vis. Sci. 37, 5255–5255 (1996).

1995 (5)

J. S. Schuman, M. R. Hee, A. V. Arya, T. Pedut-Kloizman, C. A. Puliafito, J. G. Fujimoto, and E. A. Swanson, “Optical coherence tomography: a new tool for glaucoma diagnosis,” Curr. Opin. Ophthalmol. 6, 89–95 (1995).

J. S. Schuman, M. R. Hee, C. A. Puliafito, C. Wong, T. Pedut-Kloizman, C. P. Lin, E. Hertzmark, J. A. Izatt, E. A. Swanson, and J. G. Fujimoto, “Quantification of nerve fiber layer thickness in normal and glaucomatous eyes using optical coherence tomography,” Arch. Ophthalmol. 113, 586–596 (1995).

M. R. Hee, C. A. Puliafito, C. Wong, J. S. Duker, E. Reichel, J. S. Schuman, E. A. Swanson, and J. G. Fujimoto, “Optical coherence tomography of macular holes,” Ophthalmology annual 102, 748–756 (1995).

A. F. Fercher, C. K. Hitzenberger, G. Kamp, and S. Y. Elzaiat, “Measurement of intraocular distances by backscattering spectral interferometry,” Opt. Commun. 117, 43–48 (1995).
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1994 (1)

J. A. Izatt, M. R. Hee, E. A. Swanson, C. P. Lin, D. Huang, J. S. Schuman, C. A. Puliafito, and J. G. Fujimoto, “Micrometer-scale resolution imaging of the anterior eye in vivo with optical coherence tomography,” Arch. Ophthalmol. 112, 1584–1589 (1994).

1993 (2)

1991 (1)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254, 1178–1181 (1991).
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1990 (1)

1988 (1)

A. Grinvald, R. D. Frostig, E. Lieke, and R. Hildesheim, “Optical imaging of neuronal-activity,” Physiol. Rev. 68, 1285–1366 (1988).

1950 (1)

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B. R. Biedermann, W. Wieser, C. M. Eigenwillig, G. Palte, D. C. Adler, V. J. Srinivasan, J. G. Fujimoto, and R. Huber, “Real time en face Fourier-domain optical coherence tomography with direct hardware frequency demodulation,” Opt. Lett. 33, 2556–2558 (2008).
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B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wojtkowski, “Fuchs’ endothelial dystrophy in 830 nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 198–200 (2009).

J. J. Kaluzny, M. Wojtkowski, B. L. Sikorski, M. Szkulmowski, A. Szkulmowska, T. Bajraszewski, J. G. Fujimoto, J. S. Duker, J. S. Schuman, and A. Kowalczyk, “Analysis of the outer retina reconstructed by high-resolution, three-dimensional spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 40, 102–108 (2009).

B. J. Kaluzny, A. Szkulmowska, M. Szkulmowski, T. Bajraszewski, A. Kowalczyk, and M. Wcjtkowski, “Fuchs’ endothelial dystrophy in 830 nm spectral domain optical coherence tomography,” Ophthalmic Surg. Lasers Imaging 39, S83–S85 (2008).

T. Bajraszewski, M. Wojtkowski, M. Szkulmowski, A. Szkulmowska, R. Huber, and A. Kowalczyk, “Improved spectral optical coherence tomography using optical frequency comb,” Opt. Express 16, 4163–4176 (2008).
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B. J. Kaluzny, W. Fojt, A. Szkulmowska, T. Bajraszewski, M. Wojtkowski, and A. Kowalczyk, “Spectral optical coherence tomography in video-rate and three-dimensional imaging of contact lens wear,” Optom. Vis. Sci. 84, 1104–1109 (2007).

T. Bajraszewski, M. Wojtkowski, A. Szkulmowska, W. Fojt, M. Szkulmowski, and A. Kowalczyk, “Fourier-domain optical coherence tomography using optical frequency comb,” Proc. SPIE 6429, 64291F (2007).

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M. Wojtkowski, T. Bajraszewski, P. Targowski, and A. Kowalczyk, “Real-time in vivo imaging by high-speed spectral optical coherence tomography,” Opt. Lett. 28, 1745–1747(2003).
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B. J. Vakoc, R. M. Lanning, J. A. Tyrrell, T. P. Padera, L. A. Bartlett, T. Stylianopoulos, L. L. Munn, G. J. Tearney, D. Fukumura, R. K. Jain, and B. E. Bouma, “Three-dimensional microscopy of the tumor microenvironment in vivo using optical frequency domain imaging,” Nat. Med. 15, 1219–1223 (2009).

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G. J. Tearney, B. E. Bouma, S. A. Boppart, B. Golubovic, E. A. Swanson, and J. G. Fujimoto, “Rapid acquisition of in vivo biological images by use of optical coherence tomography,” Opt. Lett. 21, 1408–1410 (1996).
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T. Bajraszewski, M. Wojtkowski, A. Szkulmowska, W. Fojt, M. Szkulmowski, and A. Kowalczyk, “Fourier-domain optical coherence tomography using optical frequency comb,” Proc. SPIE 6429, 64291F (2007).

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R. U. Maheswari, H. Takaoka, R. Homma, H. Kadono, and M. Tanifuji, “Implementation of optical coherence tomography (OCT) in visualization of functional structures of cat visual cortex,” Opt. Commun. 202, 47–54 (2002).
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B. E. Bouma, S. H. Yun, B. J. Vakoc, M. J. Suter, and G. J. Tearney, “Fourier-domain optical coherence tomography: recent advances toward clinical utility,” Curr. Opin. Biotechnol. 20, 111–118 (2009).
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