Abstract

Raman spectroscopy is a laser spectroscopic method that reveals detailed chemical information about a sample. Point-wise scanning produces chemical maps of heterogeneous samples such as biological tissue without prior staining. However, the intrinsically low Raman scattering cross-sections result in long acquisition times, despite the high excitation intensity in the focus. Here, we present a novel technique termed light sheet Raman micro-spectroscopy, which is an imaging spectrometer attached to a light sheet illumination microscope that can quickly acquire large hyperspectral Raman images. This method is more than 5 times faster than conventional approaches, while reducing the local excitation intensity over 300 fold. We show a stack of hyperspectral Raman images of a zebrafish eye with 1024×1024×50 spectra (17 min/slice) to demonstrate how the application of spontaneous Raman micro-spectroscopy can be extended to biomedical research and diagnosis based on directly utilizing the molecular information present in the sample.

© 2016 Optical Society of America

1. INTRODUCTION

Identifying and understanding the structure of cells and tissue require studying their chemical properties in great detail while leaving them undisturbed. Raman spectroscopy, a widely applied laser spectroscopic method, is one such approach that has found its way into almost all natural sciences [1]. The strength of Raman spectroscopy lies in its high molecular selectivity, i.e., Raman scattered light carries detailed chemical information about the sample. Furthermore, when combined with the ability to image, this molecular fingerprint information can be used to generate spatial chemical maps of complex heterogeneous systems like biological cells or tissue. Obtaining a specific chemical contrast without the need to label the samples makes this technique very attractive for many applications in biomedical research and clinical diagnosis. In the past few years, there has been a substantial increase in the application of Raman spectroscopy in the wet sciences [2,3].

Hyperspectral Raman imaging, also known as Raman micro-spectroscopy, refers to an umbrella of techniques based on Raman scattering where the spectral information is acquired for each pixel [4]. Traditionally, these spectra are collected sequentially, as in the case of confocal Raman microscopy. Because Raman scattering exhibits weak scattering cross-sections, the process of data acquisition is extremely slow. This is the major limitation of Raman spectroscopy in the analysis of cells and tissue, e.g., to identify tumor margins [2]. For sufficient signal quality, one needs about 10 seconds per pixel at an irradiance of 1.2mW/μm2 to scan a zebrafish sample using a commercial confocal Raman microscope (WiTec α300 equipped with a 532 nm Laser and a 60×1.0 NA water immersion objective).

Increasing the laser power can speed up the measurement. However, this is not advisable for sensitive biological samples, as local heating effects can destroy the sample due to coagulation or carbonization. A disadvantage of the pixel-scanning approach is the needless illumination of the out-of-focus region (the majority of a thick sample) [Fig. 1(a)], which causes unwanted signal and heat. A large field of view confocal acquisition at high numerical aperture (NA) needs a long exposure time even if a high transversal resolution is not required because increasing the scan step size would result in spatial under-sampling and cause aliasing artifacts. Because Raman signals from tissue are extremely faint, even weak processes such as autofluorescence or Raman scattering from optical elements can easily dominate the detected signal.

 figure: Fig. 1.

Fig. 1. Method of LSRM. (a) Out-of-focus illumination comparison between confocal scanning with one high-NA objective, and (b) light sheet illumination with a separate objective for illumination. (c) Stable, high-étendue interferometer for high acceptance angle with two inputs and outputs, consisting of two reduced-corner cube reflectors and two beam splitters. (d) Long-term stable embedding for the sample S in agarose. It is attached to a spoon-like metal structure for imaging in water immersion. (e) Optical setup of illumination path with a 2 W, 577 nm laser (yellow) and Fourier-transform imaging spectrometer (top view of (c)) (red). Sample S is in its water-filled chamber (gray), and reference laser is not shown here for clarity. (f) Principle of under-sampling the interferogram based on a typical Raman spectrum consisting of C-H and O-H modes, fingerprint and background fluorescence with an excitation wavelength of 577 nm (see Supplement 1 for details of interferogram acquisition).

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To improve the speed of hyperspectral Raman data acquisition, a line-scanning approach has been previously combined with a slit detection aperture and a two-dimensional (2D) spectrograph, detecting hyperspectral information at every illumination line [57]. This approach spreads the in-focus illumination and thus the thermal load to the sample at the expense of a reduced confocal sectioning ability, but the other aforementioned disadvantages still remain present.

In this work, we present light sheet Raman micro-spectroscopy (LSRM), a combination of light sheet illumination with a novel Fourier transform (FT)-based spectral imaging method that provides full spectral Raman information for every image point. Such an implementation of Raman spectroscopy has not been demonstrated so far, to the best of our knowledge. With this setup, we have acquired hyperspectral Raman data volumes consisting of >4 million Raman spectra at 18cm1 resolution of polystyrene (PS) and poly(methyl methacrylate) (PMMA) beads in less than 3.5 min. Even an increased spectral resolution of 4.4cm1 requires less than 14 min to record. We also demonstrate the application of our method for biological samples by imaging a zebrafish embryo at the same high resolution.

2. METHOD OF LSRM

The technique of light sheet illumination microscopy, originally invented for Rayleigh scattering [8] and later employed for fluorescence [light sheet fluorescence microscopy (LSFM)] [9,10], uses the excitation light more efficiently along the illumination sheet. A whole in-focus plane of a transparent tissue can be imaged at once by illuminating it with a sheet of light from the side without causing out-of-focus haze or heating [Fig. 1(b)]. The light sheet technique offers the conceptual advantages of massively reduced sample heating for a given amount of in-focus signal. The unwanted signal from optical components is also reduced as light sheet setups feature separate illumination and detection beam paths. It thus makes a lot of sense to employ the light sheet geometry for Raman imaging. However, in the implementations of light sheet-based Raman imaging previously demonstrated [11,12], the recorded spectral information was limited to only a few selected wavelength bands. The biggest challenge, therefore, in combining the light sheet excitation geometry with Raman imaging is to find an efficient way of extracting the hyperspectral information for utilizing the molecular fingerprint.

To successfully combine light sheet illumination with Raman spectroscopy, we started with a modified OpenSPIM [13] design equipped with a 2 W, 577 nm laser [Fig. 1(e)] (see Supplement 1). With this geometry, we generate a light sheet of a thickness between 3.1 μm (center) and 10.5 μm (edge), for a field of view of 325μm×325μm with a maximum irradiance of 1.7mW/μm2 (center). The sample is observed orthogonal to the illumination light sheet with a 0.8 NA water immersion objective (lateral spatial resolution under optimal conditions is 375 nm).

In order to obtain the hyperspectral information, we employ a Fourier transform-based imaging method that calls for a robust interferometer for spectral decoding. Sagnac interferometers are frequently used because of their robustness due to the common path setup [14]. However, their spectral resolution is comparably low, especially when a large field of view is required [15,16]. A Michelson interferometer seems to be a better approach, but the pitch and yaw stability while moving one of the interferometer mirrors would be extraordinarily hard to maintain. Thus, we developed a new type of stable, high-étendue interferometer for achieving large optical travel ranges and angles of acceptance (patent DE102014011668A1). It is inherently robust against mechanical stress in all degrees of freedom except along the direction of travel, which we tightly control by feedback with a 543 nm helium–neon reference laser.

This interferometer consists of two silver-coated, reduced-corner cube reflectors made of solid glass and two 50% beam splitters [Fig. 1(c)] placed in the infinity-corrected beam path between the high-NA imaging objective and its corresponding tube lens [Fig. 1(e)] (see Supplement 1). Using this setup, we acquire images with different optical path differences (OPDs) between the two arms while running it in step-scan mode. Due to the band-limited Raman signal, we economize the acquisition by intentionally under-sampling the interference pattern in terms of OPD (see Supplement 1), hence covering a wavelength range from 1086 to 543 nm [see Fig. 1(f)].

A spectral resolution of 0.01cm1 is achievable with a single-point FT-spectrometer under optimal conditions [17]. In the case of FT imaging spectrometers, there is a compromise between the field of view and the maximal spectral resolution; for instance, a very long OPD can cause vignetting.

Limited by its geometry, our imaging interferometer achieves a spectral resolution better than 1cm1. However, a spectral resolution of 4cm1 is normally sufficient for biomedical Raman spectroscopy.

An ideal sample for LSRM should be transparent, non-fluorescent, Raman active, and sturdily embedded. In our work, the samples were embedded in 2% standard agarose and attached to a spoon-like metal structure [Fig. 1(d)], as this proved to be more stable against a change in temperature compared to the standard procedure [10] (see Supplement 1). Since at the 577 nm wavelength, the excitation autofluorescence often overwhelms the weak Stokes-scattered Raman signal, we carefully bleach the focal region of interest (ROI) as well as its vicinity in advance by illuminating it with slowly increasing power prior to the actual data acquisition.

3. DATA PROCESSING

We usually record spectrally under-sampled [Fig. 1(f)], symmetrical stacks of 1024 different OPDs to achieve 18cm1 spectral resolution or 4096 different OPDs, resulting in 4.4cm1 spectral resolution. Depending on the sample, the typical exposure times for every OPD image are between 200 ms and 1 s. A chain of post-processing steps is necessary: correcting for offset and flat field, correction for local sample drift, estimation and subtraction of slowly fading residual fluorescence, and a pixel-wise Fourier transformation (see Supplement 1).

These processing steps of the interferograms are followed by processing in spectral space. In order to reduce the noise, we extract the real part of our phase-corrected complex spectra. For correcting the phase, we use an approach without a priority knowledge of the instrument-phase function by only taking advantage of the slowly varying phase in space and wavelength. Furthermore, we correct for the angle-dependent OPD scaling in the interferometer, which would otherwise lead to position-dependent spectral scales (see Supplement 1).

A known challenge for light sheet microscopy is the shadow effect caused by local absorption or scattering [18,19]. In the case of water-embedded biological samples, we can assume a homogeneous concentration of water. Thus, a very efficient way of removing such unwanted shadows is dividing by the averaged water signal between 3250 and 3825cm1 from the same dataset. Although this does not prevent the light sheet from spreading along the z-direction, it significantly improves the image quality (Fig. 3).

4. RESULTS

A. Polymer Sample

Figure 2 displays the Fourier-transformed hyperspectral data containing 2048×2048 Raman spectra of 2.2 μm PS and 6.0 μm PMMA beads embedded in agarose and recorded at a constant spectral resolution of 4.4cm1 in 14 min. In order to keep the amount of data to a size that can be handled, we either processed the spatially binned raw data containing one million spectra with 325nm×325nm×4.4cm1 resolution or 1024 out of the 4096 raw images resulting in a hyperspectral image containing four million spectra at 163nm×163nm×18cm1 resolution (corresponds to 3.5 min of exposure). In terms of the scanning speed of one single point at 18cm1 spectral resolution, this would compare to a scanning time of 49 μs per spectrum. This scanning speed is usually not achievable with a confocal Raman microscope due to the limited excitation intensities and readout time of the detectors.

 figure: Fig. 2.

Fig. 2. LSRM with polymer beads. Result of a 2048×2048 Raman spectra containing measurement of PS and PMMA beads embedded in agarose and obtained using 4096 different OPDs. (a) 2048×2048 spectra at 18cm1 resolution and 3.5 min total exposure; (red) ring-breathing mode of PS from 1000cm1 to 1018cm1, (green) C-H stretch mode in PMMA, band from 2941 to 2959cm1, and (blue) water signal from 3193 to 3660cm1. (b) 16 times magnified ROI as indicated in (a). (c) Mean of spectra at 4.4cm1 resolution and 14 min total exposure of all PS (red) and PMMA beads (blue). (d) One out of one million 2×2 binned spectra at 4.4cm1 resolution of PS (red) and PMMA beads (blue). Excitation polarization dependence of averaged (e) PS beads and (f) PMMA beads in the illumination plane 0° (red) and orthogonal to the plane 90° (blue).

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An important issue in imaging spectroscopy is the spatial homogeneity of the spectral response. Taking two spectra of the same sample and placing them in different positions should lead to the same peak positions. In other words: averaging over many spectra should under equal conditions, not lead to spectral broadening. Comparing the Raman peak at 1001cm1 of PS in Figs. 2(c) and 2(d) indeed shows no significant difference in width or shape, thanks to the previous correction for the angle-dependent OPD scaling.

The perpendicular geometry of the light sheet illumination scheme allows us to use two qualitatively different illumination polarizations, namely, in plane (0°) and orthogonal to the plane (90°). Figures 2(e)2(f) show the Raman spectra of PS and PMMA from two hyperspectral images recorded for both polarizations. Notice the different shapes of the spectra and the reduction of the completely symmetrical ring-breathing mode of PS at 1001cm1. As we change only the polarization properties of excitation and not of detection, we do not expect a complete disappearance of symmetrical modes. In Raman spectroscopy, different polarizations can ease chemical identification. The grating-free spectrometer setup [Fig. 1(c)] supports the homogeneous detection efficiency of polarization.

B. Three-Dimensional Imaging of a Zebrafish

The zebrafish (Danio rerio) is a common sample for genetics and developmental biology because of its transparency. Here, we use a three-day-old pigment-reduced embryo fixed in paraformaldehyde and washed in a phosphate-buffered saline solution to demonstrate the applicability of our LSRM approach for biological specimens. Figure 3 shows three Raman bands from the hyperspectral image of a zebrafish eye. We reduced the shadow effects by applying the water normalization method as described above. The method usually performs well on Raman signals, except when the light sheet is excessively spreading out of the illumination plane, as caused by the high refractive index of the eye lens [compare Figs. 3(a) and 3(b) with 3(d) and 3(e)]. Sometimes, bright stripes can arise in the fluorescence signal after normalization, which we attribute to the inhomogeneous bleaching of the residual fluorescence.

 figure: Fig. 3.

Fig. 3. Reducing light sheet shadows. Raman images of the eye of a zebrafish embryo (Danio rerio) embedded in 2% standard agarose. Maximal irradiance: 870μW/μm2, spectral resolution: 4.4cm1, total exposure time: 1 h 8 min. (a) Raman peak from 2941 to 3017cm1, (b) from 2851 to 2910cm1, (c) water signal from 3247cm1 to 3826cm1, (d) reducing shadows by normalizing (a) by (c), and (e) normalized (b) by (c).

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To identify constituents without using prior knowledge about the Raman spectra of the components, we employ a non-negative matrix factorization algorithm (NMF) [20]. It results in a linear data representation of the Raman spectra [21]. By using the fingerprint region from 500 to 1850cm1 and the C-H stretch modes from 2750 to 3100cm1 of the hyperspectral image, the NMF constrained to five components yields separated Raman spectra [Fig. 4(a)]. By comparing the spectra with reference Raman spectra [3], we could assign four of the five NMF spectra to collagen, lipids, DNA, and water [see Fig. 4(a)]. The corresponding NMF images are visualized directly through the red, green and blue (RGB) channels in Fig. 5(a).

 figure: Fig. 4.

Fig. 4. Raman spectra of the eye of a zebrafish embryo. (a) NMF-based spectral unmixing of a single hyperspectral image at 4.4cm1 spectral resolution after 250000 iterations corresponding to Fig. 5(a). (b) Comparison of the SNR of our LSRM and a state-of-the-art confocal Raman microscope based on a zebrafish eye lens sample (see Table 1). (green) Averaged spectral LSRM data of 6×6 raw pixels (1μm×1μm). Equivalent time of acquisition in terms of scanning: 39 ms. (red) Same as green, but with a Gauss filter of σ=4.4cm1. (blue) Averaged spectral data of a confocal microscope of 2×2 raw pixels (1μm×1μm) with an acquisition time of 175 ms. Compare the shape of the peak at 1001cm1 and the noise on top of the water shoulder between 3200 and 3500cm1.

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 figure: Fig. 5.

Fig. 5. Unmixed 3D Raman image of a zebrafish eye. Corresponding color images of three NMF channels: (red) collagen-like fingerprint, (green) lipid-like fingerprint, (blue) DNA-like fingerprint. (a) Image NMF result at 4.4cm1 spectral resolution; corresponding spectra shown in Fig. 4(a). (b) Selected xy-slice of the 3D hyperspectral image stack at 18cm1 resolution after NMF based unmixing [Fig. 4(a)] and 3D deconvolution of each color channel. (c) Selected yz-slice. (d) Selected xz-slice.

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Tables Icon

Table 1. Experimental Parameters of the Presented LRSM Setup Compared to a Confocal Raman Microscope

The decomposition found by the NMF of the single slice was applied to other layers of the zebrafish measured at coarser spectral resolutions. To match the spectral resolution of the NMF result (4.4cm1) to a three-dimensional (3D) stack containing 50 hyperspectral images at an 18cm1 spectral resolution (17 min of exposure for each slice), the decomposed spectra were binned spectrally four times. After separating the whole volume into five grayscale 3D images, we applied a 3D deconvolution with a simulated point spread function to each (see Supplement 1). Three of the five are color-coded in RGB and visualized in Figs. 5(b)5(d) and as a serial slice video (see Supplement 1, Visualization 1).

5. COMPARISON OF LSRM AND CONFOCAL RAMAN MICRO-SPECTROSCOPY

To assess the performance of our LSRM method, we compared the results from our LSRM setup and a state-of-the-art confocal Raman setup equipped with a fiber-coupled grating spectrometer (WiTec α300). With LSRM, we needed 14 min to acquire 4 million Raman spectra with sufficient quality from a polymer sample at 4.4cm1 resolution, whereas the confocal microscope at its fastest scan speed would need 51 h. This would yield a 213 times speed advantage.

However, this comparison is not very even-handed because the signal-to-noise ratio (SNR) and irradiance were not accounted for.

For an application-oriented comparison, we used the collagen-rich eye lens of a zebrafish as a test sample (Fig. 5). Table 1 lists a comparison of the various experimental parameters.

At first glance, the confocal setup exhibits a better SNR (421 versus 151) determined by the water region between 3200 and 3500cm1 of the spectra averaged over 1μm2 [see Fig. 4(b)]. However, a closer look revealed sharper spectra of our LSRM. Upon making the spectra qualitatively comparable by appropriate Gaussian low-pass filtering of our LSRM data (σ=4.4cm1), we arrive at an SNR of 311. The SNR comparison of both approaches is not straightforward due to uniform noise in the Fourier-transform spectra, which leads to a signal-dependent SNR [22].

To estimate the speed advantage of our LSRM in comparison with the confocal technique applied to the zebrafish sample, we have to take all the experimental boundary conditions into account. Neglecting the efficiency of the optical components and the interference contrast, we end up, under equalized experimental conditions, with a ratio of total exposure times t^L and t^C of (sub index L for LSRM, sub index C for confocal microscope)

sr=[t^Lt^C]1=[λLλC]4·[NALNAC]2·[sLsC]2·[SNRLSNRC]2·[tLtC]1sr=[577nm532nm]4·[10.8]2·[325μm40μm]2·[3142]2·[280s4096s]=5.3.

Here, we consider the slight difference in excitation wavelength λ for scattering cross-section and the numerical aperture of both systems. Further, we normalize the field of view (s×s) to equal areas of 1μm2 and incorporate the different SNRs for this area. Of course, this speed ratio factor sr cannot be seen as a general assessment of the two techniques because it strongly depends on the experimental conditions and requirements. For example, it is proportional to the field of view, since tL is independent of sL, whereas tC scales linearly with sC. It is a major advantage that while we increase the speed by light sheet illumination, we simultaneously reduce the maximum illumination irradiance over 340 fold in comparison to spot scanning (Table 1). This reduction in maximal local brightness is not possible with the slit scanning technique [7] mentioned above. If for a confocal microscope the irradiance would be limited to 2mW/μm2, as claimed in [7], LSRM would increase the acquisition speed 780 fold. The choice of the Raman excitation wavelength depends strongly on the absorbance and fluorescence of the sample. In our case, we bleached the fluorescence in both cases, while the absorbance should be roughly the same for both wavelengths.

6. DISCUSSION

Light sheet Raman micro-spectroscopy is a novel method used to record large hyperspectral Raman images of biological samples. It is more than 5 times faster than a conventional confocal Raman microscope. The use of light sheet illumination also reduces the irradiance by a factor of 340, which is very beneficial when working with sensitive biological samples. A further advantage of our illumination geometry is the separation between the illumination and detection beam paths, hence avoiding the need for CaF sample holders to minimize the glass Raman background signals.

For the experimental realization, we developed a stable, high-étendue imaging spectrometer, a robust technique to embed our samples in water immersion, and a reliable approach to remove light sheet-induced shadows by exploiting the Raman signal of the embedding water. During the raw data processing, we correct for the sample drift, spectral phase, fluorescence decay, and high incidence angle effects of the interferometer. For data visualization, we employ spectral unmixing and deconvolution techniques.

As with most light sheet-imaging techniques, LSRM also requires the sample to be appropriately transparent for improved penetration depth. Zebrafish is therefore a very widely used biological sample. The image quality is degraded by two effects: scattering of the illumination and scattering of the emitted Raman light. The achievable image depth, just as in LSFM, depends heavily on the optical inhomogeneity within the sample such as fat cells in the gut or, in our case, the lens of the zebrafish eye. Upon close inspection, image degradation is visible behind the lens at a depth of 150 μm in our stack.

However, it is also possible to make several other biological cells and tissues artificially transparent via optical clearing methods. To homogenize the refractive index, most clearing methods either remove the lipids that offer interesting chemical Raman contrasts or use organic solvents as embedding media that result in strong Raman peaks that swamp the interesting fingerprint region. This also highlights the importance of choosing the right embedding media. Besides being clearly separated from the ROI in the Raman spectrum, an ideal embedding medium should remain robust for long acquisition times. Agarose, a well-known embedding medium for LSFM [10], is a good choice, but tends to melt locally in the presence of highly absorptive samples. In the future, we intend to experiment with different embedding media, such as Cygel [23], and a robust cooling strategy for the sample during long exposure conditions. A lot of research in chemistry is currently dedicated towards improving clearing methods and synthesizing better embedding media [24].

Various aspects of the LSRM technique could be evolved further by incorporating different light sheet illumination geometries. For instance, lattice light sheets [25] can be combined with LSRM to optimize sectioning. Similarly to enhance contrast and confocality, a scanned Gauss–Bessel illumination to generate the light sheet and a de-scanned detection followed by a detection slit [26] and a 2D spectral detector could be used. To further reduce the illumination-induced shadow effects, a pivot scan [27] could be applied. Structured illumination approaches [28] can also be extended to Raman imaging to improve the spatial resolution beyond Abbe’s limit. The use of different excitation wavelengths (e.g., 785 nm, a standard wavelength for life-science Raman spectroscopy) to reduce absorption and possibly autofluorescence is another option worth exploring.

The image reconstruction of the current hyperspectral FT imaging method presupposes a rigid sample. We already account for a global sample drift during the measurement, which could be further developed to compensate for movements and deformations. However, arbitrary 3D motion during a single-plane hyperspectral data acquisition (here, 17 min) is difficult to compensate for and can lead to the broadening of the Raman peaks and the degradation of the spatial contrast.

Improvement of the detection system can also enhance the efficiency of LSRM. Using the second output of the interferometer as an additional imaging source would double the photon efficiency and enable us to correct for time-depended fluctuations of the illumination laser. It may also be rewarding to use other full-field hyperspectral techniques based on framing, windowing, or pushbroom [22] that promise a better SNR performance and reduced acquisition time, albeit compromising on the field of view.

Although this technique does not yet allow hyperspectral Raman imaging at video rate, the major advantage is an acquisition time independent of the field of view, enabling observations of Raman spectra of different cells and different cell compartments simultaneously. This provides a much better insight on the chemical composition of highly heterogeneous organs. It would now be possible to investigate cancer biopsies of metastasis and the chemical gradients of guidance molecules in developmental biology spread over a large distance, as well as larger cells whose different parts are located in different chemical environment (e.g., neurons in the brain).

Funding

Carl-Zeiss-Stiftung; Leibniz-Gemeinschaft.

Acknowledgment

We thank Christian Matthäus for his help with the measurements of the confocal system. Sapna Shukla and Ulrich Leischner are thanked for their attentive review of the manuscript. We thank Thomas Büttner and Robert Kretschmer for the help in preparing mechanical parts. The publication of this article was funded by the Open Access Fund of the Leibniz Association.

 

See Supplement 1 for supporting content.

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References

  • View by:

  1. J. M. Chalmers and P. R. Griffiths, Handbook of Vibrational Spectroscopy (Wiley, 2002).
  2. C. Krafft and J. Popp, “The many facets of Raman spectroscopy for biomedical analysis,” Anal. Bioanal. Chem. 407, 699–717 (2012).
    [Crossref]
  3. C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
    [Crossref]
  4. T. Dieing, O. Hollricher, and J. Toporski, Confocal Raman Microscopy (Springer, 2011), Vol. 158.
  5. M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
    [Crossref]
  6. C. J. De Grauw, C. Otto, and J. Greve, “Line-scan Raman microspectrometry for biological applications,” Appl. Spectrosc. 51, 1607–1612 (1997).
    [Crossref]
  7. J. Qi and W.-C. Shih, “Performance of line-scan Raman microscopy for high-throughput chemical imaging of cell population,” Appl. Opt. 53, 2881–2885 (2014).
    [Crossref]
  8. H. Siedentopf and R. Zsigmondy, “Uber Sichtbarmachung und Größenbestimmung ultramikoskopischer Teilchen, mit besonderer Anwendung auf Goldrubingläser,” Ann. Phys. 315, 1–39 (1903).
    [Crossref]
  9. A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
    [Crossref]
  10. J. Huisken and D. Y. R. Stainier, “Selective plane illumination microscopy techniques in developmental biology,” Development 136, 1963–1975 (2009).
    [Crossref]
  11. Y. Oshima, H. Sato, H. Kajiura-Kobayashi, T. Kimura, K. Naruse, and S. Nonaka, “Light sheet-excited spontaneous Raman imaging of a living fish by optical sectioning in a wide field Raman microscope,” Opt. Express 20, 16195–16204 (2012).
    [Crossref]
  12. I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
    [Crossref]
  13. P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
    [Crossref]
  14. J. Zhao and R. L. McCreery, “Multichannel Fourier transform Raman spectroscopy: combining the advantages of CCDs with interferometry,” Appl. Spectrosc. 50, 1209–1214 (1996).
    [Crossref]
  15. R. G. Sellar and G. D. Boreman, “Limiting aspect ratios of Sagnac interferometers,” Opt. Eng. 42, 3320–3325 (2003).
    [Crossref]
  16. Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
    [Crossref]
  17. P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry, 2nd ed. (Wiley, 2007).
  18. U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
    [Crossref]
  19. J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
    [Crossref]
  20. D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, eds. (MIT, 2001), pp. 556–562.
  21. H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).
  22. R. G. Sellar and G. D. Boreman, “Comparison of relative signal-to-noise ratios of different classes of imaging spectrometer,” Appl. Opt. 44, 1614–1624 (2005).
    [Crossref]
  23. R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
    [Crossref]
  24. D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
    [Crossref]
  25. B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).
  26. E. Baumgart and U. Kubitscheck, “Scanned light sheet microscopy with confocal slit detection,” Opt. Express 20, 21805–21814 (2012).
    [Crossref]
  27. J. Huisken and D. Y. R. Stainier, “Even fluorescence excitation by multidirectional selective plane illumination microscopy (mSPIM),” Opt. Lett. 32, 2608–2610 (2007).
    [Crossref]
  28. T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
    [Crossref]

2015 (1)

D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
[Crossref]

2014 (2)

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

J. Qi and W.-C. Shih, “Performance of line-scan Raman microscopy for high-throughput chemical imaging of cell population,” Appl. Opt. 53, 2881–2885 (2014).
[Crossref]

2013 (1)

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

2012 (5)

J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
[Crossref]

C. Krafft and J. Popp, “The many facets of Raman spectroscopy for biomedical analysis,” Anal. Bioanal. Chem. 407, 699–717 (2012).
[Crossref]

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

Y. Oshima, H. Sato, H. Kajiura-Kobayashi, T. Kimura, K. Naruse, and S. Nonaka, “Light sheet-excited spontaneous Raman imaging of a living fish by optical sectioning in a wide field Raman microscope,” Opt. Express 20, 16195–16204 (2012).
[Crossref]

E. Baumgart and U. Kubitscheck, “Scanned light sheet microscopy with confocal slit detection,” Opt. Express 20, 21805–21814 (2012).
[Crossref]

2011 (2)

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

2010 (2)

I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
[Crossref]

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

2009 (1)

J. Huisken and D. Y. R. Stainier, “Selective plane illumination microscopy techniques in developmental biology,” Development 136, 1963–1975 (2009).
[Crossref]

2007 (2)

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

J. Huisken and D. Y. R. Stainier, “Even fluorescence excitation by multidirectional selective plane illumination microscopy (mSPIM),” Opt. Lett. 32, 2608–2610 (2007).
[Crossref]

2006 (1)

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

2005 (1)

2003 (1)

R. G. Sellar and G. D. Boreman, “Limiting aspect ratios of Sagnac interferometers,” Opt. Eng. 42, 3320–3325 (2003).
[Crossref]

1997 (1)

1996 (1)

1993 (1)

A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
[Crossref]

1990 (1)

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

1903 (1)

H. Siedentopf and R. Zsigmondy, “Uber Sichtbarmachung und Größenbestimmung ultramikoskopischer Teilchen, mit besonderer Anwendung auf Goldrubingläser,” Ann. Phys. 315, 1–39 (1903).
[Crossref]

Adal, T.

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

Arora, R.

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

Barman, I.

I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
[Crossref]

Baumgart, E.

Bembenek, J. N.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Betzig, E.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Bohme, R.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Boreman, G. D.

R. G. Sellar and G. D. Boreman, “Comparison of relative signal-to-noise ratios of different classes of imaging spectrometer,” Appl. Opt. 44, 1614–1624 (2005).
[Crossref]

R. G. Sellar and G. D. Boreman, “Limiting aspect ratios of Sagnac interferometers,” Opt. Eng. 42, 3320–3325 (2003).
[Crossref]

Bowden, M.

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

Burns, D. H.

A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
[Crossref]

Chalmers, J. M.

J. M. Chalmers and P. R. Griffiths, Handbook of Vibrational Spectroscopy (Wiley, 2002).

Chavel, P.

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

Chen, B.-C.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Cichocki, A.

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

Davidson, M. W.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

De Grauw, C. J.

de Haseth, J. A.

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry, 2nd ed. (Wiley, 2007).

Dieing, T.

T. Dieing, O. Hollricher, and J. Toporski, Confocal Raman Microscopy (Springer, 2011), Vol. 158.

Dietzek, B.

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

Dodt, H. U.

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

Eliceiri, K. W.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Emge, D.

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

English, B. P.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Fehrenbach, J.

J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
[Crossref]

Ferrec, Y.

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

Fritz-Laylin, L.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Galbraith, C. G.

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Galbraith, J. A.

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Gao, L.

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Gardiner, D. J.

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

Gerrard, D. L.

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

Greve, J.

Griffiths, P. R.

J. M. Chalmers and P. R. Griffiths, Handbook of Vibrational Spectroscopy (Wiley, 2002).

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry, 2nd ed. (Wiley, 2007).

Grill, S. W.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Hammer, J. A.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Hollricher, O.

T. Dieing, O. Hollricher, and J. Toporski, Confocal Raman Microscopy (Springer, 2011), Vol. 158.

Huisken, J.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

J. Huisken and D. Y. R. Stainier, “Selective plane illumination microscopy techniques in developmental biology,” Development 136, 1963–1975 (2009).
[Crossref]

J. Huisken and D. Y. R. Stainier, “Even fluorescence excitation by multidirectional selective plane illumination microscopy (mSPIM),” Opt. Lett. 32, 2608–2610 (2007).
[Crossref]

Janetopoulos, C.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Kajiura-Kobayashi, H.

Kiehart, D. P.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Kimura, T.

Krafft, C.

C. Krafft and J. Popp, “The many facets of Raman spectroscopy for biomedical analysis,” Anal. Bioanal. Chem. 407, 699–717 (2012).
[Crossref]

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

Kubitscheck, U.

Lee, D. D.

D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, eds. (MIT, 2001), pp. 556–562.

Legant, W. R.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Leischner, U.

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

Li, H.

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

Lichtman, J. W.

D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
[Crossref]

Lippincott-Schwartz, J.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Liu, J.

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

Liu, Z.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Lorenzo, C.

J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
[Crossref]

McCreery, R. L.

Milkie, D. E.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Mimori-Kiyosue, Y.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Mitchell, D. M.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Mullins, R. D.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Naruse, K.

Nonaka, S.

Oshima, Y.

Otto, C.

Petrov, G. I.

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

Pitrone, P. G.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Planchon, T. A.

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

Popp, J.

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

C. Krafft and J. Popp, “The many facets of Raman spectroscopy for biomedical analysis,” Anal. Bioanal. Chem. 407, 699–717 (2012).
[Crossref]

Preibisch, S.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Qi, J.

Reymann, A.-C.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Rice, G.

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

Richardson, D. S.

D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
[Crossref]

Ritter, A. T.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Romero, D. P.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Sato, H.

Sauer, H.

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

Schierloh, A.

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

Schindelin, J.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Schmitt, M.

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

Sellar, R. G.

R. G. Sellar and G. D. Boreman, “Comparison of relative signal-to-noise ratios of different classes of imaging spectrometer,” Appl. Opt. 44, 1614–1624 (2005).
[Crossref]

R. G. Sellar and G. D. Boreman, “Limiting aspect ratios of Sagnac interferometers,” Opt. Eng. 42, 3320–3325 (2003).
[Crossref]

Seung, H. S.

D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, eds. (MIT, 2001), pp. 556–562.

Seydoux, G.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Shao, L.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Shih, W.-C.

Siedentopf, H.

H. Siedentopf and R. Zsigmondy, “Uber Sichtbarmachung und Größenbestimmung ultramikoskopischer Teilchen, mit besonderer Anwendung auf Goldrubingläser,” Ann. Phys. 315, 1–39 (1903).
[Crossref]

Singh, G. P.

I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
[Crossref]

Spelman, F. A.

A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
[Crossref]

Stainier, D. Y. R.

J. Huisken and D. Y. R. Stainier, “Selective plane illumination microscopy techniques in developmental biology,” Development 136, 1963–1975 (2009).
[Crossref]

J. Huisken and D. Y. R. Stainier, “Even fluorescence excitation by multidirectional selective plane illumination microscopy (mSPIM),” Opt. Lett. 32, 2608–2610 (2007).
[Crossref]

Stuyvenberg, L.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Taboury, J.

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

Tan, K. M.

I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
[Crossref]

Tomancak, P.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Toporski, J.

T. Dieing, O. Hollricher, and J. Toporski, Confocal Raman Microscopy (Springer, 2011), Vol. 158.

Tulu, U. S.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Voie, A. H.

A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
[Crossref]

Wang, J. T.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Wang, K.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Wang, W.

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

Weber, M.

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Weiss, P.

J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
[Crossref]

Wu, X. S.

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Yakovlev, V. V.

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

Zhao, J.

Zieglgänsberger, W.

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

Zsigmondy, R.

H. Siedentopf and R. Zsigmondy, “Uber Sichtbarmachung und Größenbestimmung ultramikoskopischer Teilchen, mit besonderer Anwendung auf Goldrubingläser,” Ann. Phys. 315, 1–39 (1903).
[Crossref]

Anal. Bioanal. Chem. (1)

C. Krafft and J. Popp, “The many facets of Raman spectroscopy for biomedical analysis,” Anal. Bioanal. Chem. 407, 699–717 (2012).
[Crossref]

Ann. Phys. (1)

H. Siedentopf and R. Zsigmondy, “Uber Sichtbarmachung und Größenbestimmung ultramikoskopischer Teilchen, mit besonderer Anwendung auf Goldrubingläser,” Ann. Phys. 315, 1–39 (1903).
[Crossref]

Appl. Opt. (2)

Appl. Spectrosc. (2)

Cell (1)

D. S. Richardson and J. W. Lichtman, “Clarifying tissue clearing,” Cell 162, 246–257 (2015).
[Crossref]

Development (1)

J. Huisken and D. Y. R. Stainier, “Selective plane illumination microscopy techniques in developmental biology,” Development 136, 1963–1975 (2009).
[Crossref]

IEEE Trans. Image Process. (1)

J. Fehrenbach, P. Weiss, and C. Lorenzo, “Variational algorithms to remove stationary noise: applications to microscopy imaging,” IEEE Trans. Image Process. 21, 4420–4430 (2012).
[Crossref]

J. Biomed. Opt. (2)

R. Arora, G. I. Petrov, J. Liu, and V. V. Yakovlev, “Improving sensitivity in nonlinear Raman microspectroscopy imaging and sensing,” J. Biomed. Opt. 16, 021114 (2011).
[Crossref]

C. Krafft, B. Dietzek, M. Schmitt, and J. Popp, “Raman and coherent anti-Stokes Raman scattering microspectroscopy for biomedical applications,” J. Biomed. Opt. 17, 040801 (2012).
[Crossref]

J. Microsc. (1)

A. H. Voie, D. H. Burns, and F. A. Spelman, “Orthogonal-plane fluorescence optical sectioning: three-dimensional imaging of macroscopic biological specimens,” J. Microsc. 170, 229–236 (1993).
[Crossref]

J. Raman Spectrosc. (2)

M. Bowden, D. J. Gardiner, G. Rice, and D. L. Gerrard, “Line-scanned micro Raman-spectroscopy using a cooled CCD imaging detector,” J. Raman Spectrosc. 21, 37–41 (1990).
[Crossref]

I. Barman, K. M. Tan, and G. P. Singh, “Optical sectioning using single-plane-illumination Raman imaging,” J. Raman Spectrosc. 41, 1099–1101 (2010).
[Crossref]

J. VLSI Signal Processing (1)

H. Li, T. Adal, W. Wang, D. Emge, A. Cichocki, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy,” J. VLSI Signal Processing 48, 83–97 (2007).

Nat. Methods (2)

T. A. Planchon, L. Gao, D. E. Milkie, M. W. Davidson, J. A. Galbraith, C. G. Galbraith, and E. Betzig, “Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination,” Nat. Methods 8, 417–423 (2011).
[Crossref]

P. G. Pitrone, J. Schindelin, L. Stuyvenberg, S. Preibisch, M. Weber, K. W. Eliceiri, J. Huisken, and P. Tomancak, “OpenSPIM: an open-access light-sheet microscopy platform,” Nat. Methods 10, 598–599 (2013).
[Crossref]

Opt. Eng. (2)

R. G. Sellar and G. D. Boreman, “Limiting aspect ratios of Sagnac interferometers,” Opt. Eng. 42, 3320–3325 (2003).
[Crossref]

Y. Ferrec, J. Taboury, H. Sauer, and P. Chavel, “Optimal geometry for Sagnac and Michelson interferometers used as spectral imagers,” Opt. Eng. 45, 115601 (2006).
[Crossref]

Opt. Express (2)

Opt. Lett. (1)

PLoS ONE (1)

U. Leischner, A. Schierloh, W. Zieglgänsberger, and H. U. Dodt, “Formalin-induced fluorescence reveals cell shape and morphology in biological tissue samples,” PLoS ONE 5, e10391 (2010).
[Crossref]

Science (1)

B.-C. Chen, W. R. Legant, K. Wang, L. Shao, D. E. Milkie, M. W. Davidson, C. Janetopoulos, X. S. Wu, J. A. Hammer, Z. Liu, B. P. English, Y. Mimori-Kiyosue, D. P. Romero, A. T. Ritter, J. Lippincott-Schwartz, L. Fritz-Laylin, R. D. Mullins, D. M. Mitchell, A.-C. Reymann, J. N. Bembenek, R. Bohme, S. W. Grill, J. T. Wang, G. Seydoux, U. S. Tulu, D. P. Kiehart, and E. Betzig, “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science 346, 1257998 (2014).

Other (4)

D. D. Lee and H. S. Seung, “Algorithms for non-negative matrix factorization,” in Advances in Neural Information Processing Systems, T. K. Leen, T. G. Dietterich, and V. Tresp, eds. (MIT, 2001), pp. 556–562.

P. R. Griffiths and J. A. de Haseth, Fourier Transform Infrared Spectrometry, 2nd ed. (Wiley, 2007).

J. M. Chalmers and P. R. Griffiths, Handbook of Vibrational Spectroscopy (Wiley, 2002).

T. Dieing, O. Hollricher, and J. Toporski, Confocal Raman Microscopy (Springer, 2011), Vol. 158.

Supplementary Material (2)

NameDescription
Supplement 1: PDF (1182 KB)      Supplemental document
Visualization 1: MP4 (14812 KB)      Unmixed 3D Raman image of a zebrafish eye.

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Figures (5)

Fig. 1.
Fig. 1. Method of LSRM. (a) Out-of-focus illumination comparison between confocal scanning with one high-NA objective, and (b) light sheet illumination with a separate objective for illumination. (c) Stable, high-étendue interferometer for high acceptance angle with two inputs and outputs, consisting of two reduced-corner cube reflectors and two beam splitters. (d) Long-term stable embedding for the sample S in agarose. It is attached to a spoon-like metal structure for imaging in water immersion. (e) Optical setup of illumination path with a 2 W, 577 nm laser (yellow) and Fourier-transform imaging spectrometer (top view of (c)) (red). Sample S is in its water-filled chamber (gray), and reference laser is not shown here for clarity. (f) Principle of under-sampling the interferogram based on a typical Raman spectrum consisting of C-H and O-H modes, fingerprint and background fluorescence with an excitation wavelength of 577 nm (see Supplement 1 for details of interferogram acquisition).
Fig. 2.
Fig. 2. LSRM with polymer beads. Result of a 2048 × 2048 Raman spectra containing measurement of PS and PMMA beads embedded in agarose and obtained using 4096 different OPDs. (a)  2048 × 2048 spectra at 18 cm 1 resolution and 3.5 min total exposure; (red) ring-breathing mode of PS from 1000 cm 1 to 1018 cm 1 , (green) C-H stretch mode in PMMA, band from 2941 to 2959 cm 1 , and (blue) water signal from 3193 to 3660 cm 1 . (b) 16 times magnified ROI as indicated in (a). (c) Mean of spectra at 4.4 cm 1 resolution and 14 min total exposure of all PS (red) and PMMA beads (blue). (d) One out of one million 2 × 2 binned spectra at 4.4 cm 1 resolution of PS (red) and PMMA beads (blue). Excitation polarization dependence of averaged (e) PS beads and (f) PMMA beads in the illumination plane 0° (red) and orthogonal to the plane 90° (blue).
Fig. 3.
Fig. 3. Reducing light sheet shadows. Raman images of the eye of a zebrafish embryo (Danio rerio) embedded in 2% standard agarose. Maximal irradiance: 870 μW / μm 2 , spectral resolution: 4.4 cm 1 , total exposure time: 1 h 8 min. (a) Raman peak from 2941 to 3017 cm 1 , (b) from 2851 to 2910 cm 1 , (c) water signal from 3247 cm 1 to 3826 cm 1 , (d) reducing shadows by normalizing (a) by (c), and (e) normalized (b) by (c).
Fig. 4.
Fig. 4. Raman spectra of the eye of a zebrafish embryo. (a) NMF-based spectral unmixing of a single hyperspectral image at 4.4 cm 1 spectral resolution after 250000 iterations corresponding to Fig. 5(a). (b) Comparison of the SNR of our LSRM and a state-of-the-art confocal Raman microscope based on a zebrafish eye lens sample (see Table 1). (green) Averaged spectral LSRM data of 6 × 6 raw pixels ( 1 μm × 1 μm ). Equivalent time of acquisition in terms of scanning: 39 ms. (red) Same as green, but with a Gauss filter of σ = 4.4 cm 1 . (blue) Averaged spectral data of a confocal microscope of 2 × 2 raw pixels ( 1 μm × 1 μm ) with an acquisition time of 175 ms. Compare the shape of the peak at 1001 cm 1 and the noise on top of the water shoulder between 3200 and 3500 cm 1 .
Fig. 5.
Fig. 5. Unmixed 3D Raman image of a zebrafish eye. Corresponding color images of three NMF channels: (red) collagen-like fingerprint, (green) lipid-like fingerprint, (blue) DNA-like fingerprint. (a) Image NMF result at 4.4 cm 1 spectral resolution; corresponding spectra shown in Fig. 4(a). (b) Selected x y -slice of the 3D hyperspectral image stack at 18 cm 1 resolution after NMF based unmixing [Fig. 4(a)] and 3D deconvolution of each color channel. (c) Selected y z -slice. (d) Selected x z -slice.

Tables (1)

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Table 1. Experimental Parameters of the Presented LRSM Setup Compared to a Confocal Raman Microscope

Equations (1)

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sr = [ t ^ L t ^ C ] 1 = [ λ L λ C ] 4 · [ NA L NA C ] 2 · [ s L s C ] 2 · [ SNR L SNR C ] 2 · [ t L t C ] 1 sr = [ 577 nm 532 nm ] 4 · [ 1 0.8 ] 2 · [ 325 μm 40 μm ] 2 · [ 31 42 ] 2 · [ 280 s 4096 s ] = 5.3.

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