Abstract

Diffuse reflectance technique is popular in the study of tissue physiology through the change in optical properties in a noninvasive manner. Diffuse reflected light intensity is commonly collected either from a single distance with spectral measurement or from a single wavelength with different spatial distances. Improving existing systems is necessary in order to obtain information from greater depths and in smaller volumes. In this paper, we propose a fast and compact fiber probe-based diffuse reflectance method for combining the spectral measurements in the range of 400–950 nm and spatial information up to 1.33 mm from the illumination source. First, we chose the most appropriate analysis model for the proposed distances between the fiber probe and tested it on solid phantoms with varying scattering and absorption components. The measurements are compared to the scattering coefficients according to Mie theory and the absorption according to spectrophotometer measurements. Next, we measured two-layer phantoms with constant scattering and absorption contrast in different layer thicknesses. We extracted the penetration depth from the measured effective absorption coefficient. In the near-IR, we were able to detect the absorption coefficient of the bottom phantom layer behind a top layer of up to 5 mm. We achieved a maximum penetration depth of 5.7 mm for 5 mm top layer thickness at 900 nm. Our fiber probe diffuse reflectance system can be used in the near future for skin lesion detection in clinical studies.

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

The interpretation of optical properties from a turbid medium is a challenging task in the biomedical optics field. A sophisticated instrument is required to extract the quantitative information about the chemical components, scattering elements, and refractive index of the medium [1]. These components will help us understand how the optical properties are related to light propagation in a turbid medium. Once the behavior of light in a turbid medium is measured, it is possible to extract the absorption coefficient (µa) and the reduced scattering coefficient (µs’ = µs (1-g)), where µs is the scattering coefficient and g is the anisotropy (g = < cosθ >, typical g values for biological tissues are between 0.65 to 0.95) [2]. All of these properties are wavelength-dependent [3,4]. Biological tissues can be characterized by their optical properties and these properties can be effectively determined by using diffusion approximation [5,6]. Photon transport in a scattering tissue is generally modeled using the radiative transfer equation (RTE), which offers a solution to the highly scattering medium [7,8].

Several optical techniques were developed to measure the tissue optical properties. The most common method is to measure the diffusely reflected (DR) intensity through spectral or spatial dependency. DR measurement from tissue-mimicking solid and liquid phantoms are well-established for calibrating the device to known absorption coefficients or scattering coefficients of the phantoms [9,10]. Optical fibers are leading components in medically specialized instrumentation [11]. Using these fibers, a wide variety of DR probes were investigated for tissue analysis. The fiber probe’s design for measuring DR intensity for tissue characterization reported up to now consisting of large source-detector distances (SDDs) and a short SSD measurement. A short SDD fiber probe is a more demanding appliance in clinical utilization since the majority of melanoma occurs in the superficial epithelium tissue layers, and the typical thickness is < 1 mm [12]. In short SDDs, probe design has optical fiber bundles with one illumination fiber and one or more collection fibers. Some propose a circular design [1317] and some of them are designed in a linear manner [18,19]. In a circular bundle fiber probe design, most of the work that has been done till now uses a circularly arranged fibers (1-to-7) bundle where one center fiber is surrounded by six fibers. In this fiber probe design, the middle fiber is used for illumination and the surrounding six fibers collect the reflected intensity or vice versa. In the latter, the six fibers collect the average intensity where the probe was positioned on the sample and it is less efficient in quantifying the spatial information of the components present in the medium due to limited penetration depth. Here the penetration depth cannot be increased by increasing the fiber diameter. In the linearly arranged fiber probe design, the intensity collection is unidirectional from the sample.

In this paper, we designed a fiber probe in such a way that it should differentiate and evaluate the absorption and scattering properties in tissue using DR measurements. The design of the fiber probe is a linear measurement using a circular fiber probe DR setup for both spectral and spatial analysis of tissue-optical properties (reduced scattering or absorption coefficients, as well as penetration depth). From this fiber probe, we measured the intensity from individual fibers so we can track any abnormalities in the sample of each fiber position due to small SDD. First, we modeled the fiber probe DR to demonstrate the dependence of the reflected light intensity profile on the optical properties measured between 400 nm to 950 nm. This model was tested on homogeneous solid phantoms with varying concentrations of scattering and absorption coefficients. The optical properties were extracted using the diffusion theory [6]. In our experiment, the maximum source-detector distance was 1.33 mm. We confirmed which value of the theoretical model gives the best fit to our data using phantoms with known optical properties [20]. Next, we prepared two-layer solid phantoms where the top and bottom layers had the same scattering, but the bottom layer had additional absorption. These phantoms had the same total thickness but a varying top layer thickness. We used these phantoms to assess the penetration depth of the proposed fiber probe.

2. Materials and method

2.1 Photon distribution in tissue

The propagation of light in a turbid medium can be described by the RTE which is complicated to solve. Considering the regime where µs’ >> µa (common in biological tissues) the RTE can be simplified, which is known as the diffusion approximation (Farrell et al. 1992) [6]). In this model, diffraction, interference, coherence, nonlinearity, and polarization effects are neglected. Under these conditions, the resulting diffusion equation is as follows:

$$\frac{{\partial \Phi (\vec{r},t)/c}}{{\partial t}} + {\mu _a}\Phi (\vec{r},t) - D{\nabla ^2}\Phi (\vec{r},t) = S(\vec{r},t)$$
where Ф is the fluence rate, S represents the source, and D is the diffusion coefficient: D = 1/[3(µas’)]. The diffusion approximation to the RTE is used to recover the optical properties from DR measurement. Two approximations are made in the derivation of the diffusion equation from the RTE: First, the expansion of the radiance is limited to the first-order spherical harmonics. Second, the fractional change in the current density in one transport mean free path is much less than a unity. Therefore, these two approximations can be generalized into a single condition i.e., scattering events are much more probable than absorption events (µs’ >> µa) [5]. Also, we require the observation point to be sufficiently far (few millimeters) from sources and boundaries [21]. Under these conditions, the RTE can be simplified to the DR equation:
$$R(\rho ) = \left( {\frac{{{C_1}}}{{{\rho^m}}}} \right)\,{\textrm{exp} ^{ - {\mu _{eff}}.\,\rho }}$$
where C1 is a constant, depending on the optical properties of the medium and the sizes of the source and detector apertures, m is the power of ρ, which depends on ρ’s range and the ratio 1/µas’ and µeff denotes the effective attenuation coefficient given by:
$${\mu _{eff}} = \sqrt {\frac{{{\mu _a}}}{D}} = \sqrt {3{\mu _a}({\mu _a} + \mu _s^{\prime})}$$

DR model enables us to calculate the absorption coefficient and the reduced scattering coefficient from the diffuse reflectance R (ρ) of the measured tissue as long as the power m in the diffusion equation is known. The radiation field inside and around the tissue depends on the fundamental properties; these are the irradiation geometry and boundary conditions. Then Eq. (2) can be further simplified as:

$$\ln (R(\rho ).{\rho ^m}) = {C_2} - {\mu _{eff}}.\rho$$

Therefore, determining the power m is the first required step to establish a quantitative value of the effective attenuation coefficient for DR measurements. The values m = ½, 1, 2 depend on the scattering coefficients and the range over which optical properties can be determined. By fitting to a single exponential Groenhuis et al. [22] showed good agreement between experimental results and theory for ρ between 0.3 and 1.0 mm using a value of m = ½. Patterson et al. and Ankri et al. [19,23] showed for ρ greater than 2 mm using m = 2 that the slope is equal to -µeff. In the radial distance between these, m = 1 yields a straight line used by Schmitt et al. [24,25].

Under the assumption µa << µs, the effective attenuation coefficient is reduced to:

$${\mu _{eff}} \approx \sqrt {3{\mu _a}\mu _s^{\prime}}$$

Using Eq. (5) one can calculate the absorption coefficients by knowing the reduced scattering coefficient, or calculate the reduced scattering coefficients by knowing the absorption coefficient. If we know the optical properties such as µs’ and µa we can calculate the light penetration depth in the sample.

2.2 Experimental setup

The DR experimental setup consists of a 1-to-7 fan-out optical fiber bundle from Thorlabs (BF76HS01). In this fiber bundle, one fiber is used for illumination and the remaining six fibers for collection. The light source is a tungsten-halogen lamp (HL-2000-HP-FHSA with 20 W output power, Ocean Insight). A spectrometer is used for optical measurement (FLAME-T-VIS-NIR-Spectrometer, Ocean Insight) in the wavelength range from 350 to 1000 nm.

The size of the fiber probe bundle is 1.9 mm, with each fiber having a core diameter of 600 µm and 0.39 numerical aperture (NA). Here we are not using the middle fiber for illumination; rather we chose one side fiber (fiber denoted by S in the probe design in Fig. 1) as a source fiber. First, we measured the distance between the individual fibers using a charge-coupled device (CCD) camera. Using Fiji software (ImageJ), the distance between the individual fibers were measured. The measured average inter-fiber distances (measured from the center of fibers to each of the remaining fibers in the probe design in Fig. 1) are ρ1 = 0.63 mm, ρ2 = 0.67 mm, ρ3 = 0.71 mm, ρ4 = 1.15 mm, ρ5 = 1.18 mm, ρ6 = 1.33 mm.

 

Fig. 1. Schematic of fiber probe diffuse reflectance experimental setup: Tungsten halogen HL-2000-HP-FHSA (350–1000 nm) light source is connected to one of the 1-to-7 fan-out fibers of the optic bundle (denoted S), while the reaming six fibers are used for collection. The probe is placed on the phantom, and a FLAME-T-VIS-NIR-Spectrometer is connected to each of the output fibers to record the re-emitted signal.

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Before the sample measurements, the light source and dark spectra were calibrated against a diffuse reflectance standard Spectralon (Newport). After the calibration of the system, the spectra were recorded in the wavelength range from 350–1000 nm at six fiber distances (ρ1, ρ2, ρ3, ρ4, ρ5, and ρ6 composing the ρ axis). The experiment was repeated for four sequential measurements from different positions on the sample.

The intensity as a function of the distance ρ was used to extract the optical coefficients according to the diffusion theory.

2.3 Tissue mimicking solid phantom preparation

We prepared three types of tissue-mimicking solid phantoms with different concentrations: Single-layer (1L) phantoms with scattering only, 1L phantoms with scattering and absorption, and two-layer (2L) phantoms. The optical properties according to the wavelengths were calculated using Mie theory [10,20,26].

The first type of 1L phantoms was prepared by varying Intralipid (IL) concentrations (0.75, 1, 1.25, 1.5, 1.75, and 2%). Here IL (Intralipid 20% Emulsion, Sigma-Aldrich, Israel) was used as a scattering component and 1% agarose powder (Agarose - low gelling temperature, Sigma-Aldrich, Israel) was used to convert the solution into a gel (Agarose will allow solidification of the sample). Double Distilled water (DDW) was heated to the temperature of ∼ 65°C, while the 2% agarose was slowly added to the water. Once the agarose melted completely, IL and additional DDW was added to the solution and mixed for 1 min with a continuous stir and at a mixing temperature of ∼ 40 °C to make a homogeneous solution. Note, the 2% Agarose first melted into half of the amount of the final volume, and then it was diluted to 1% following the additional IL and DDW [27]. The homogeneous solution is poured into tissue culture plates (with a diameter of 60 mm and a thickness of 10 mm) and cooled under vacuum conditions (to avoid air bubbles).

The second type of 1L phantoms was prepared with different ink concentrations (1, 2, 3, 5, and 8×10−5). Here India Black Ink (Royal Talens-490 ml), as an absorbing component, in addition to a fixed scattering of 1% IL were used to create the phantoms. The same preparation procedure (as mentioned above) was followed for preparing phantoms with different absorption coefficients and constant scattering.

In the third type, two-layer phantoms were prepared with a constant reduced scattering coefficient (1% IL) top layer (thickness denote as T). The bottom layer had a constant absorption coefficient (3×10−5 India black ink) and a constant reduced scattering coefficient (1% IL) (bottom layer thickness denote as B). Two-layer phantoms were prepared with a total thickness of 10 mm by varying the thickness of the top layer from T = 1 mm to T = 5 mm. At first, the bottom layer solution (3×10−5 Ink+1% IL) was prepared and solidified in the culture plates (with a diameter of 60 mm) using the same preparation procedure. Then the top layer solution (1% IL) was prepared and added on top of the solid bottom layer at room temperature. Finally, the two-layer phantoms were cooled under vacuum conditions to receive a solid two-layer phantom.

3. Results

3.1 Extraction of reduced scattering coefficients from one-layer solid phantoms

Fiber probe diffuse reflectance spectroscopic experiments were performed for six phantoms with different IL concentrations to extract the spatially distributed diffuse reflected photon around the injection point in homogeneous tissue-mimicking solid phantoms. The collected reflected light intensity has quantitative information about the optical properties of the tissue. The reflected light intensity profiles of different scattering phantoms according to Eq. (4) shown in Fig. 2(a) are the logarithmic of the product between the measured intensity and distance [ln (R(ρ) × ρ)] vs. distance at 500 nm for six IL concentrations (0.75%, 1%, 1.25%, 1.5%, 1.75%, and 2% correspond to the upward-pointing triangle, circle, diamond, star, downward-pointing triangle and hexagonal in Fig. 2(a)).

 

Fig. 2. Process of extracting the reduced scattering coefficient of 1L phantoms. Six solid phantoms with varying Intralipid concentrations 0.75, 1, 1.25, 1.5, 1.75, 2% (upward-pointing triangle, circle, diamond, star, downward-pointing triangle, and hexagonal) were prepared. (a) Measured reflected light intensity from phantoms as a function of the distance ρ (at 500 nm) and linear fit (solid lines). (b) Calculated µs’ from the slope of the linear fits presented in (a) according to Eq. (4) as a function of wavelength. The solid line indicates the reduced scattering coefficients based on Mie theory [20]. The error bars indicate the standard deviations (< 0.12 mm−1) over the four sequential measurements from different positions on the sample.

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The slope of each phantom in the linear part (in a distance between 0.7 and 1.33 mm) was extracted, where the progression in the slope increase with the concentration of Intralipid (solid lines in Fig. 2(a) represents the linear fit). We ignore the first two points while determining the slope because the diffusion theory is not accurate when the source-detector distance is too small and our detection range is not in the sub-diffusive regime [2830]. The parameter m = 1 gives the best fit to the measured spatial reflectance data from the phantoms (in accordance to Schmitt et al. [24]). From these slope values, we calculated the scattering coefficients using Eq. (5) by the knowledge of the absorption coefficient (here water and IL are the absorbing components and IL shows a more significant absorption coefficient of 0.11 mm−1 at 500 nm). The extracted µs’ values at 500 nm are as follows: 1.16 mm−1, 1.63 mm−1, 2.0 mm−1, 2.48 mm−1, 2.69 mm−1, 3.32 mm−1 are compare to the calculated µs’ values from Mie theory [20] as follows :1.21 mm−1, 1.61 mm−1, 2.01 mm−1, 2.41 mm−1, 2.81 mm−1, 3.21 mm−1. The experimentally measured reduced scattering values match Mie theory.

Figure 2(b) shows the experimentally computed reduced scattering coefficient as a function of wavelength from 400 nm to 950 nm (upward-pointing triangle, circle, diamond, star, downward-pointing triangle, and hexagonal in Fig. 2(b)) compared to the data calculated using Mie theory [20] (solid lines in Fig. 2(b)). The extracted data are in good agreement with the theoretical values. The scattering coefficient monotonically decreases with wavelength. The standard deviations (< 0.12 mm−1) were calculated from four experimental trials.

The experimental results demonstrate the dependence of the scattering coefficient on the wavelength of interest. As the scattering coefficient increases, there is a rise in the slope of the reflected light intensity (Fig. 2(a) upper arrow). This indicates the change in intrinsic optical properties of the phantom, due to an increase in the density of scattering particles per unit volume.

 

Fig. 3. Extracted absorption coefficient as a function of wavelength and ink concentrations with constant scattering (1% Intralipid). The solid lines indicate the absorption coefficient values measured in a spectrophotometer. (a) Absorption coefficient as a function of the concentration of ink at different wavelengths (400 nm, 450 nm, 500 nm, 550 nm, 600 nm, 700 nm, 800 nm correspond to the upward-pointing triangle, star, diamond, square, hexagonal, downward-pointing triangle, circle). (b) Absorption coefficient as a function of wavelength (0, 1, 2, 3, 5, and 8×10−5 correspond to circle, star, upward-pointing triangle, square, hexagonal, diamond). Inset: the image of homogeneous single layer phantoms with constant scattering concentration and increasing absorption concentration, measured in the graph (standard deviations < 0.10 mm−1).

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3.2 Determination of absorption coefficients from one-layer phantoms

Fiber probe diffuse reflectance spectroscopic measurements were carried out for five prepared one-layer homogeneous phantoms with different ink concentrations (0, 1, 2, 3, 5, and 8×10−5) with constant scattering concentration (1%) (preparation procedure is detailed in section 2.3 and the experimental setup described in section 2.2). The data was extracted between the wavelength range from 400 nm to 950 nm. The reflected light intensity profile was measured and the slopes of the linear region were extracted (explained in section 3.1, Fig. 2(a)). Here we use the known scattering to extract the absorption from Eq. (5).

Figure 3(a) presents the extracted µa as a function of ink concentrations at different wavelengths (400 nm, 450 nm, 500 nm, 550 nm, 600 nm, 700 nm, 800 nm correspond to the upward-pointing triangle, star, diamond, square, hexagonal, downward-pointing triangle, circle in Fig. 3(a)). The absorption spectrum of different ink concentrations was measured using the spectrophotometer. The absorption coefficient of each phantom was determined according to the concentration of ink in each solution (in Fig. 3(a) the solid line indicates the µa extracted from the spectrophotometer). From Fig. 3(a) we can observe the linear relationship between the absorption coefficient and ink concentration (the downward arrow indicates the increment in the wavelength). The experimental results show that the predicted analytical diffusion model is valid; the absorption coefficient matches the expected value and increases with the concentration of ink at a specific wavelength.

Figure 3(b) is the calculated absorption coefficient as a function of wavelength with respect to ink concentrations (0, 1, 2, 3, 5, and 8×10−5 correspond to circle, star, upward-pointing triangle, square, hexagonal, diamond), and the filled black circle indicates the control (1% IL and no ink). The solid line is the absorption measured from the spectrophotometer. Note that we observe two significant peaks in the experimental data at the wavelengths of 780 nm and 1 µm, which do not exist in the spectrophotometer measurements. These two peaks correspond to the absorption spectrum of lipid [31].

3.3 Estimation of effective absorption coefficient and penetration depth in two-layer phantoms

We prepared two-layered phantoms with varying top layer thickness according to the preparation procedure detailed above (section 2.3). The reflected light was measured using the same technique as detailed in section 3.1. We calculated the effective absorption coefficient for different thickness of the prepared phantoms using Eq. (5) (Fig. 4(a)) over a spectral range between 400 nm to 900 nm (top-layer thickness: 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm correspond to a downward-pointing triangle, diamond, star, hexagonal, upward-pointing triangle, circle in Fig. 4(a) and control with a constant scattering and a thickness of 10 mm). As increasing the thickness of the top layer (downward-pointing arrow in Fig. 4(a)), there is a reduction in the net absorption coefficients. We noticed that the sharp decay in the absorption coefficient from 400 nm to 600 nm, and afterward there is a rise in the absorption coefficient in the higher wavelength region [32]. From Fig. 4(a), we can observe that there is an influence of incoming light into the bottom layer from 532 nm onwards for larger top layer thickness (3, 4, 5 mm). There is a strong indication that the longer wavelengths can penetrate deeper than the shorter wavelengths (in the therapeutic window). When the structure of the sample varies the behavior of light within the medium is different because it is directly related to the optical properties of the sample itself (both absorption and scattering coefficients). This can be observed in Fig. 3(b) is the extracted absorption coefficient from the single-layer phantoms made with varying the concentration of absorption component (1, 2, 3, 5, and 8×10−5) with a constant scattering component (1% Intralipid). Figure 4(a) presents the extracted effective absorption coefficient from the two-layer phantom made with constant absorption component (3×10−5) and constant scattering component (1% Intralipid) but with varying the top layer thickness (1, 2, 3, 4, and 5mm).

 

Fig. 4. Extracting the effective absorption coefficient and penetration depth from DR measurements of 2L phantoms (with a total thickness of 10 mm and constant scattering of 1% IL). (a) Extracted effective absorption coefficient as a function of wavelength with respect to the top-layer thickness of the sample (top layer thickness:1 mm, 2 mm, 3 mm, 4 mm, and 5 mm and control with a thickness of 10 mm (1% IL) correspond to the downward-pointing triangle, diamond, star, hexagonal, upward-pointing triangle, circle). (Standard deviation < 0.01 mm−1). (b) Calculated penetration depth according to Eq. (9) as a function of wavelength with respect to the sample thickness compared to 2δ according to the top layer (black solid) and bottom layer (dashed lines) optical coefficients. The solid and dashed lines are controls of the single-layer phantom, where the solid line represents a phantom with the properties of the top layer penetration depth and the dashed line represents the properties of the bottom layer. Inset: the image of phantoms with a varying top layer thickness (mm).

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We can estimate the optical penetration depth with the knowledge of the scattering and absorption coefficient of the tested sample. Many methods define the penetration depth, or calculating light penetration depth have been described [33]. According to diffusion theory, light penetration depth δ is defined as the depth at which the intensity of light within the material falls by 1/e (about 37%) of its initial value at the surface, and it is calculated as the reciprocal of the effective attenuation coefficient [34]:

$$\delta = \frac{1}{{{\mu _{eff}}}}$$

The penetration depth will help us understand the propagation of light in a multilayer tissue at different wavelengths. The absorption coefficient represented in Fig. 4(a) is actually an effective absorption coefficient, and it was influenced by the two layers. Since the top layer thickness (T) is known, and we wish to find how deep light can penetrate the bottom layer (B) in the spectral range from 400 to 900 nm, we propose as follows. Let us describe the effective absorption coefficient as a weighted average of the two layers:

$${\mu _{aeff}} = {\mu _{a\_IL}}\frac{T}{{T + B}} + {\mu _{a\_Ink + IL}}\frac{B}{{T + B}}$$
where µa_IL is the absorption due to Intralipid concentration (top layer), µa_Ink+IL is the absorption due to ink and Intralipid concentration (bottom layer). Since we extracted µaeff, from the above Eq. (7) we can calculate the B by rearranging the terms as follows:
$$B = \frac{{T({\mu _{a\_IL}} - {\mu _{aeff}})}}{{({\mu _{aeff}} - {\mu _{a\_Ink + IL}})}}$$

Once we extract B using Eq. (8), we can find the distance at which light traveled into the two-layer phantom by adding the top layer thickness and the equation becomes:

$$T + B \propto \delta$$

The total (top and bottom layer) distance light traveled in the phantom was calculated using Eq. (9) in the spectral range from 400 to 900 nm (points in Fig. 4(b) top-layer thickness: 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm correspond to a downward-pointing triangle, diamond, star, hexagonal, upward-pointing triangle). The maximum distance light traveled in a two-layer phantom of thickness 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm corresponds to the penetration depth of 2.95 mm, 3.45 mm, 3.73 mm, 4.53 mm, and 5.70 mm at a wavelength of 900 nm. The solid and dashed lines are controls of the single-layer phantom, where the solid line represents a phantom with the properties of the top layer (constant scattering concentration 1% IL) penetration depth and the dashed line represents the properties of the bottom layer (constant absorption (ink) of 3×10−5 and 1% (IL) scattering concentrations) penetration depth in Fig. 4(b). The scattering coefficient was calculated according to Mie theory [20], and the absorption coefficient was measured from the spectrophotometer.

In our system, the maximum penetration depth is more than δ defined by Eq. (6). The higher penetration depth is defined at a relative transmission intensity of 13% in the two-layer phantom model [34,35], corresponding to a penetration depth 2δ. In this paper, we report the penetration depth value of 2δ in our system (black solid line and dashed line in Fig. 4(b)). We calculated the penetration depth of 2.02 mm to 6.50 mm in the spectral range from 400–900 nm for constant IL concentration. In Fig. 4(b) we can clearly distinguish the influence of incoming white light in the two-layer phantom, in 1 and 2 mm top layer thickness the range of penetration depth from 1.39 mm to 2.95 mm and 2.24mm to 3.45 mm in the spectral range from 400 to 900 nm. Since the solid line represents the absorption of IL only, meaning that in the lower wavelengths, where the black line is lower than the colored lines, we do not expect sensitivity to the absorption of the bottom layer. In the highest top thicknesses (upward-pointing triangle in Fig. 4(a) corresponding to 5 mm), the absorption is only distinct above 700 nm. In the case of 3 mm top layer thickness (stars in Fig. 4(a)), the line is only noticeable above 550 nm.

We expected that in the two-layer phantom model if the light reaches the two distinct phantom layers (or biological tissue), the extracted optical property values should fall somewhere between the top and bottom layers (corresponding to solid and dashed lines in Fig. 4(b)) [2]. The calculated penetration depth in different top-layer thickness (1, 2, 3, 4, and 5 mm) phantoms falls between top and bottom layer thickness. Here the optical properties (µs’ and µa) depend on the wavelength. The penetration depth is directly related to the extracted optical properties from the sample and the incident wavelength. The errors in penetration depth are directly proportional to the errors in the measured optical properties from the phantom. Penetration depth predominantly depends on the top layer thickness (assume that the bottom layer is semi-infinite). Because the light penetration depth is a matter of definition, it is mainly considered from the sensitivity of the experimental setup, types of sample, and measurement techniques.

4. Discussion and conclusions

We have demonstrated the capability of fiber probe-based DR measurements to extract quantitative information about the concentrations and existence of scattering and absorbing components in a diffuse media using the diffusion approximation model. We confirmed in the DR model source-detector distances between 0.7 and 1.33 mm the parameter m = 1 gives the highest fit to the measured spatial and spectral reflectance data from tissue-mimicking solid phantoms.

In Fig. 2(a) as increasing the IL concentrations, there is a stronger decay in the reflected light intensity profile that directly influences the slope values. The slope values are higher as increasing the IL concentrations (Fig. 2(a)). This is a result of the change in intrinsic optical properties of the phantom, due to an increase in the density of scattering particles per unit volume. The extracted reduced scattering coefficient from the fiber probe DR measurements is in the range from 0.72 mm−1 to 3.46 mm−1 in the wavelength range between 400 nm to 950 nm with a sensitivity of 0.12 mm−1 (Fig. 2(b)).

The absorption coefficients were extracted for different ink concentrations (1×10−5, 2×10−5, 3×10−5, 5×10−5, and 8×10−5). The detected absorption coefficient from the fiber probe is in the range from 0.05 mm−1 to 1.87 mm−1 in the wavelength between 400 to 950 nm with a sensitivity of 0.10 mm−1. As expected there is a linear relationship between the ink concentrations and absorption coefficients. The absorption coefficient values are decreasing in the higher illumination wavelength. We found two absorption peaks at specific wavelengths (Fig. 3(b)) which do not exist in the spectrophotometer measurements, since these peaks correspond to the absorption spectrum of lipid reported in many articles [31]. Mie theory predicts that the reduced scattering and absorption coefficient values decrease with the increase in the wavelength [21].

The optical penetration depth was extracted for a range of wavelengths. There is a direct relation between the light penetration depth and attenuation of light in a sample. Penetration depth mainly depends on the illumination wavelength, beamwidth, optical properties of the tissue (µs’ and µa), and fiber probe geometry [36,37]. Our fiber probe DR technique can measure a maximum penetration depth of 5.70 mm for 5 mm top layer thickness at 900 nm. This indicates that there is an influence of incoming light into the bottom layer of the phantom. This study shows that 13% of the incoming light affects the method and defines the penetration depth of the fiber probe DR measurement geometry.

This shows that the fiber probe DR technique is a strong tool to measure the tissue-optical properties in a non-invasive way in the short SDD. The short SDD fiber probe represents the key towards the more general execution of DR measurement in clinical applications. For example, in cutaneous melanoma, it is essential to extract the optical properties in a specific region of tissue. Because the examination of the relevant domain is very important for extracting the tissue physiology. A wide variety of DR measurement techniques were developed previously, and most techniques required relatively large source-detector distances (up to 20 to 30 mm) and are not sensitive in the short SDD.

Ankri R et al. showed a DR system with a maximum source-detector distance of around 6 mm. The experimental set-up consists of an optical fiber for illumination and a photodetector used for collection. This system cannot measure the DR intensity close to the source (less than 1 mm) [38]. This limits their applicability to easily accessible parts like flat tissues, epithelium, and skin, superficial stroma epithelial pre-cancer and early-stage melanoma, etc. [3941]. A small SDD fiber probe DR instrument has the potential to extract quantitative tissue optical properties in non-invasive in vivo measurements in a large spectral range using a UV-vis source. Here we used a fiber probe that allows concurrent measurement at six source-detector distances even though we are not using the first two distances to assess optical parameters and found a very high agreement to theoretical values (standard deviation of scattering < 0.12 mm−1 and absorption < 0.10 mm−1). Our ultimate goal is to evolve the full potential of the current fiber probe design and optimize the SDD selection to the experimental measurement for in vivo studies. Then to extract the optical properties and increase the penetration depth for multi-layer tissue. When considering the difference between a homogeneous sample to an inhomogeneous sample having a layered structure like a skin lesion, the detection volume (sampling volume) is measured as an average probing volume. The average distance light traveled inside the medium determines on which scale the sample was investigated. We can study the deeper tissue information by adding contrast agents (example: gold nanoparticles) to the sample in a specific wavelength [38].

DR with a fiber probe may be a powerful instrument for medical applications, such as cancer detection [42], therapeutic observation [43,44], tissue characterization [45], hemoglobin observation in vital care [46], etc. [47,48]. The optical fiber geometry is crucial in the future fiber-optic tool. Large source-detector distance is preferable to the inquisition of depth volume, which allows the probe to sense deeper tissues. However, the sensitivity to a small quantity of abnormal tissue decreases with large probed volume (partial volume effect). The challenge is to develop a system with adequate probing depth and appropriate sensitivity to sight tumor margins or progressive infiltration of tumor cells.

Optical fiber probe DR may be a straightforward, worthwhile, label-free versatile technique to extract the optical properties and also imaging of the sample [49]. Still, all of these methods have many limitations. Therefore, analysis is needed to make a specific and compact optical set up to review the interaction of light with the biological sample in vivo to grasp the particular behavior of light with the biological system by qualitative and quantitative spectral and spatial information.

Disclosures

The authors have no conflicts of interest to disclose.

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1. U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003). [CrossRef]  

2. A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

3. G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001). [CrossRef]  

4. S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013). [CrossRef]  

5. L. V. Wang and H.-I. Wu, Biomedical optics: principles and imaging (John Wiley & Sons, 2012).

6. T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992). [CrossRef]  

7. M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989). [CrossRef]  

8. G. Zonios and A. Dimou, “Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties,” Opt. Express 14(19), 8661–8674 (2006). [CrossRef]  

9. J. Swartling, J. S. Dam, and S. Andersson-Engels, “Comparison of spatially and temporally resolved diffuse-reflectance measurement systems for determination of biomedical optical properties,” Appl. Opt. 42(22), 4612–4620 (2003). [CrossRef]  

10. R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997). [CrossRef]  

11. A. G. Mignani and F. Baldini, “In-vivo biomedical monitoring by fiber-optic systems,” J. Lightwave Technol. 13(7), 1396–1406 (1995). [CrossRef]  

12. R. Reif, O. A’Amar, and I. J. Bigio, “Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media,” Appl. Opt. 46(29), 7317–7328 (2007). [CrossRef]  

13. R. Groenhuis, H. A. Ferwerda, and J. Ten Bosch, “Scattering and absorption of turbid materials determined from reflection measurements. 1: Theory,” Appl. Opt. 22(16), 2456–2462 (1983). [CrossRef]  

14. B. Yu, A. Shah, V. K. Nagarajan, and D. G. Ferris, “Diffuse reflectance spectroscopy of epithelial tissue with a smart fiber-optic probe,” Biomed. Opt. Express 5(3), 675–689 (2014). [CrossRef]  

15. B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005). [CrossRef]  

16. V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016). [CrossRef]  

17. D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006). [CrossRef]  

18. T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003). [CrossRef]  

19. M. S. Patterson, E. Schwartz, and B. C. Wilson, “Quantitative reflectance spectrophotometry for the noninvasive measurement of photosensitizer concentration in tissue during photodynamic therapy,” in Photodynamic Therapy: Mechanisms, (International Society for Optics and Photonics, 1989), pp. 115–122.

20. H. J. Van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. Van Gemert, “Light scattering in lntralipid-10% in the wavelength range of 400–1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991). [CrossRef]  

21. S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992). [CrossRef]  

22. R. Groenhuis, J. Ten Bosch, and H. A. Ferwerda, “Scattering and absorption of turbid materials determined from reflection measurements. 2: Measuring method and calibration,” Appl. Opt. 22(16), 2463–2467 (1983). [CrossRef]  

23. R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012). [CrossRef]  

24. J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990). [CrossRef]  

25. R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011). [CrossRef]  

26. W. J. Wiscombe, Mie scattering calculations: Advances in technique and fast, vector-speed computer codes (National Technical Information Service, US Department of Commerce, 1979), Vol. 10.

27. D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020). [CrossRef]  

28. A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt. 35(13), 2304–2314 (1996). [CrossRef]  

29. A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017). [CrossRef]  

30. P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016). [CrossRef]  

31. M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019). [CrossRef]  

32. T. H. Pham, T. Spott, L. O. Svaasand, and B. J. Tromberg, “Quantifying the properties of two-layer turbid media with frequency-domain diffuse reflectance,” Appl. Opt. 39(25), 4733–4745 (2000). [CrossRef]  

33. T. Papaioannou, N. W. Preyer, Q. Fang, A. Brightwell, M. Carnohan, G. Cottone, R. Ross, L. R. Jones, and L. Marcu, “Effects of fiber-optic probe design and probe-to-target distance on diffuse reflectance measurements of turbid media: an experimental and computational study at 337 nm,” Appl. Opt. 43(14), 2846–2860 (2004). [CrossRef]  

34. B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990). [CrossRef]  

35. J. Qin and R. Lu, “Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique,” Postharvest Biol. Technol. 49(3), 355–365 (2008). [CrossRef]  

36. C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017). [CrossRef]  

37. R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014). [CrossRef]  

38. R. Ankri and D. Fixler, “Gold nanorods based diffusion reflection measurements: current status and perspectives for clinical applications,” Nanophotonics 6(5), 1031–1042 (2017). [CrossRef]  

39. R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015). [CrossRef]  

40. R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020). [CrossRef]  

41. T.-Y. Tseng, C.-Y. Chen, Y.-S. Li, and K.-B. Sung, “Quantification of the optical properties of two-layered turbid media by simultaneously analyzing the spectral and spatial information of steady-state diffuse reflectance spectroscopy,” Biomed. Opt. Express 2(4), 901–914 (2011). [CrossRef]  

42. N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006). [CrossRef]  

43. A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020). [CrossRef]  

44. R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018). [CrossRef]  

45. B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011). [CrossRef]  

46. S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

47. H.-W. Wang, J.-K. Jiang, C.-H. Lin, J.-K. Lin, G.-J. Huang, and J.-S. Yu, “Diffuse reflectance spectroscopy detects increased hemoglobin concentration and decreased oxygenation during colon carcinogenesis from normal to malignant tumors,” Opt. Express 17(4), 2805–2817 (2009). [CrossRef]  

48. B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008). [CrossRef]  

49. Y. S. Fawzi, A.-B. M. Youssef, M. H. El-Batanony, and Y. M. Kadah, “Determination of the optical properties of a two-layer tissue model by detecting photons migrating at progressively increasing depths,” Appl. Opt. 42(31), 6398–6411 (2003). [CrossRef]  

References

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  • |

  1. U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003).
    [Crossref]
  2. A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.
  3. G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001).
    [Crossref]
  4. S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
    [Crossref]
  5. L. V. Wang and H.-I. Wu, Biomedical optics: principles and imaging (John Wiley & Sons, 2012).
  6. T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992).
    [Crossref]
  7. M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
    [Crossref]
  8. G. Zonios and A. Dimou, “Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties,” Opt. Express 14(19), 8661–8674 (2006).
    [Crossref]
  9. J. Swartling, J. S. Dam, and S. Andersson-Engels, “Comparison of spatially and temporally resolved diffuse-reflectance measurement systems for determination of biomedical optical properties,” Appl. Opt. 42(22), 4612–4620 (2003).
    [Crossref]
  10. R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
    [Crossref]
  11. A. G. Mignani and F. Baldini, “In-vivo biomedical monitoring by fiber-optic systems,” J. Lightwave Technol. 13(7), 1396–1406 (1995).
    [Crossref]
  12. R. Reif, O. A’Amar, and I. J. Bigio, “Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media,” Appl. Opt. 46(29), 7317–7328 (2007).
    [Crossref]
  13. R. Groenhuis, H. A. Ferwerda, and J. Ten Bosch, “Scattering and absorption of turbid materials determined from reflection measurements. 1: Theory,” Appl. Opt. 22(16), 2456–2462 (1983).
    [Crossref]
  14. B. Yu, A. Shah, V. K. Nagarajan, and D. G. Ferris, “Diffuse reflectance spectroscopy of epithelial tissue with a smart fiber-optic probe,” Biomed. Opt. Express 5(3), 675–689 (2014).
    [Crossref]
  15. B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
    [Crossref]
  16. V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
    [Crossref]
  17. D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
    [Crossref]
  18. T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
    [Crossref]
  19. M. S. Patterson, E. Schwartz, and B. C. Wilson, “Quantitative reflectance spectrophotometry for the noninvasive measurement of photosensitizer concentration in tissue during photodynamic therapy,” in Photodynamic Therapy: Mechanisms, (International Society for Optics and Photonics, 1989), pp. 115–122.
  20. H. J. Van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. Van Gemert, “Light scattering in lntralipid-10% in the wavelength range of 400–1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991).
    [Crossref]
  21. S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
    [Crossref]
  22. R. Groenhuis, J. Ten Bosch, and H. A. Ferwerda, “Scattering and absorption of turbid materials determined from reflection measurements. 2: Measuring method and calibration,” Appl. Opt. 22(16), 2463–2467 (1983).
    [Crossref]
  23. R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
    [Crossref]
  24. J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
    [Crossref]
  25. R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011).
    [Crossref]
  26. W. J. Wiscombe, Mie scattering calculations: Advances in technique and fast, vector-speed computer codes (National Technical Information Service, US Department of Commerce, 1979), Vol. 10.
  27. D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
    [Crossref]
  28. A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt. 35(13), 2304–2314 (1996).
    [Crossref]
  29. A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
    [Crossref]
  30. P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
    [Crossref]
  31. M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019).
    [Crossref]
  32. T. H. Pham, T. Spott, L. O. Svaasand, and B. J. Tromberg, “Quantifying the properties of two-layer turbid media with frequency-domain diffuse reflectance,” Appl. Opt. 39(25), 4733–4745 (2000).
    [Crossref]
  33. T. Papaioannou, N. W. Preyer, Q. Fang, A. Brightwell, M. Carnohan, G. Cottone, R. Ross, L. R. Jones, and L. Marcu, “Effects of fiber-optic probe design and probe-to-target distance on diffuse reflectance measurements of turbid media: an experimental and computational study at 337 nm,” Appl. Opt. 43(14), 2846–2860 (2004).
    [Crossref]
  34. B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990).
    [Crossref]
  35. J. Qin and R. Lu, “Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique,” Postharvest Biol. Technol. 49(3), 355–365 (2008).
    [Crossref]
  36. C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
    [Crossref]
  37. R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
    [Crossref]
  38. R. Ankri and D. Fixler, “Gold nanorods based diffusion reflection measurements: current status and perspectives for clinical applications,” Nanophotonics 6(5), 1031–1042 (2017).
    [Crossref]
  39. R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
    [Crossref]
  40. R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
    [Crossref]
  41. T.-Y. Tseng, C.-Y. Chen, Y.-S. Li, and K.-B. Sung, “Quantification of the optical properties of two-layered turbid media by simultaneously analyzing the spectral and spatial information of steady-state diffuse reflectance spectroscopy,” Biomed. Opt. Express 2(4), 901–914 (2011).
    [Crossref]
  42. N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
    [Crossref]
  43. A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
    [Crossref]
  44. R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
    [Crossref]
  45. B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
    [Crossref]
  46. S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).
  47. H.-W. Wang, J.-K. Jiang, C.-H. Lin, J.-K. Lin, G.-J. Huang, and J.-S. Yu, “Diffuse reflectance spectroscopy detects increased hemoglobin concentration and decreased oxygenation during colon carcinogenesis from normal to malignant tumors,” Opt. Express 17(4), 2805–2817 (2009).
    [Crossref]
  48. B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
    [Crossref]
  49. Y. S. Fawzi, A.-B. M. Youssef, M. H. El-Batanony, and Y. M. Kadah, “Determination of the optical properties of a two-layer tissue model by detecting photons migrating at progressively increasing depths,” Appl. Opt. 42(31), 6398–6411 (2003).
    [Crossref]

2020 (3)

D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
[Crossref]

R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
[Crossref]

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

2019 (1)

M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019).
[Crossref]

2018 (1)

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
[Crossref]

2017 (3)

R. Ankri and D. Fixler, “Gold nanorods based diffusion reflection measurements: current status and perspectives for clinical applications,” Nanophotonics 6(5), 1031–1042 (2017).
[Crossref]

C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
[Crossref]

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

2016 (2)

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

2015 (1)

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

2014 (2)

B. Yu, A. Shah, V. K. Nagarajan, and D. G. Ferris, “Diffuse reflectance spectroscopy of epithelial tissue with a smart fiber-optic probe,” Biomed. Opt. Express 5(3), 675–689 (2014).
[Crossref]

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

2013 (1)

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
[Crossref]

2012 (1)

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

2011 (3)

R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011).
[Crossref]

T.-Y. Tseng, C.-Y. Chen, Y.-S. Li, and K.-B. Sung, “Quantification of the optical properties of two-layered turbid media by simultaneously analyzing the spectral and spatial information of steady-state diffuse reflectance spectroscopy,” Biomed. Opt. Express 2(4), 901–914 (2011).
[Crossref]

B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
[Crossref]

2009 (1)

2008 (2)

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

J. Qin and R. Lu, “Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique,” Postharvest Biol. Technol. 49(3), 355–365 (2008).
[Crossref]

2007 (1)

2006 (3)

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

G. Zonios and A. Dimou, “Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties,” Opt. Express 14(19), 8661–8674 (2006).
[Crossref]

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

2005 (1)

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

2004 (1)

2003 (4)

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

J. Swartling, J. S. Dam, and S. Andersson-Engels, “Comparison of spatially and temporally resolved diffuse-reflectance measurement systems for determination of biomedical optical properties,” Appl. Opt. 42(22), 4612–4620 (2003).
[Crossref]

U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003).
[Crossref]

Y. S. Fawzi, A.-B. M. Youssef, M. H. El-Batanony, and Y. M. Kadah, “Determination of the optical properties of a two-layer tissue model by detecting photons migrating at progressively increasing depths,” Appl. Opt. 42(31), 6398–6411 (2003).
[Crossref]

2001 (1)

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001).
[Crossref]

2000 (1)

1997 (1)

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

1996 (1)

1995 (1)

A. G. Mignani and F. Baldini, “In-vivo biomedical monitoring by fiber-optic systems,” J. Lightwave Technol. 13(7), 1396–1406 (1995).
[Crossref]

1992 (2)

T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992).
[Crossref]

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
[Crossref]

1991 (1)

1990 (2)

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
[Crossref]

B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990).
[Crossref]

1989 (1)

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
[Crossref]

1983 (2)

A’Amar, O.

Andersson-Engels, S.

Ankri, R.

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
[Crossref]

R. Ankri and D. Fixler, “Gold nanorods based diffusion reflection measurements: current status and perspectives for clinical applications,” Nanophotonics 6(5), 1031–1042 (2017).
[Crossref]

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011).
[Crossref]

Anuraj, K.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Arifler, D.

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

Ash, C.

C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
[Crossref]

Ayers, F.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Baiju, K. V.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Baldini, F.

A. G. Mignani and F. Baldini, “In-vivo biomedical monitoring by fiber-optic systems,” J. Lightwave Technol. 13(7), 1396–1406 (1995).
[Crossref]

Bashford, T.

C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
[Crossref]

Bender, J. E.

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Bennett, C. L.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

Bhattacharya, M.

M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019).
[Crossref]

Bigio, I. J.

Blank, T. B.

S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

Brightwell, A.

Bullard, E. A.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Bürmen, M.

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

Bykowski, J.

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001).
[Crossref]

Carnohan, M.

Chakraborty, R.

R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
[Crossref]

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
[Crossref]

Chen, C.-Y.

Clay, C. D.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Cottone, G.

Cubeddu, R.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

Dam, J. S.

Dimou, A.

Donne, K.

C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
[Crossref]

Duadi, H.

D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
[Crossref]

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

Dubec, M.

C. Ash, M. Dubec, K. Donne, and T. Bashford, “Effect of wavelength and beam width on penetration in light-tissue interaction using computational methods,” Lasers Med. Sci. 32(8), 1909–1918 (2017).
[Crossref]

Durkin, A. J.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Dutta, A.

M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019).
[Crossref]

Ediger, M. N.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

El-Batanony, M. H.

Faber, D. J.

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

Fahr, M. J.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Fang, Q.

Farrell, T. J.

T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992).
[Crossref]

Fawzi, Y. S.

Ferris, D. G.

Ferwerda, H. A.

Fixler, D.

D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
[Crossref]

R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
[Crossref]

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
[Crossref]

R. Ankri and D. Fixler, “Gold nanorods based diffusion reflection measurements: current status and perspectives for clinical applications,” Nanophotonics 6(5), 1031–1042 (2017).
[Crossref]

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011).
[Crossref]

Flock, S. T.

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
[Crossref]

Follen, M.

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

Fu, H. L.

B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
[Crossref]

Gall, J. A.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

Goth, W.

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

Grant, A. M.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Greening, G. J.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Groenhuis, R.

Hale, L. N.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Heenan, P. J.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Hennessy, R.

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

Hibst, R.

Huang, G.-J.

Jacques, S. L.

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58(11), R37–R61 (2013).
[Crossref]

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
[Crossref]

B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990).
[Crossref]

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
[Crossref]

Jayanthi, J. L.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Jiang, J.-K.

Jones, L. R.

Kadah, Y. M.

Kelly, K. M.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Kienle, A.

Kollias, N.

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001).
[Crossref]

Kornowski, R.

R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
[Crossref]

Kuech, T. F.

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Leshem-Lev, D.

R. Chakraborty, D. Leshem-Lev, R. Kornowski, and D. Fixler, “The Scattering of Gold Nanorods Combined with Differential Uptake, Paving a New Detection Method for Macrophage Subtypes Using Flow Cytometery,” Nano Lett. 20(11), 8360–8368 (2020).
[Crossref]

Li, Y.-S.

Likar, B.

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

Lilge, L.

Lin, C.-H.

Lin, J.-K.

Lo, J. Y.

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Lu, R.

J. Qin and R. Lu, “Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique,” Postharvest Biol. Technol. 49(3), 355–365 (2008).
[Crossref]

MacAulay, C. E.

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

Madhaven, J.

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Malin, S. F.

S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

Mallia, J.

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Marcu, L.

Markey, M. K.

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

Matchette, L. S.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

Mathews, A.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Melzer, S.

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

Mignani, A. G.

A. G. Mignani and F. Baldini, “In-vivo biomedical monitoring by fiber-optic systems,” J. Lightwave Technol. 13(7), 1396–1406 (1995).
[Crossref]

Moes, C. J.

Monfre, S. L.

S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

Motiei, M.

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
[Crossref]

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

Muldoon, T. J.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Mundo, A. I.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Murphy, B. W.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Nagarajan, V. K.

Naglic, P.

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

Palmer, G. M.

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Papaioannou, T.

Patterson, M. S.

A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt. 35(13), 2304–2314 (1996).
[Crossref]

T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992).
[Crossref]

M. S. Patterson, E. Schwartz, and B. C. Wilson, “Quantitative reflectance spectrophotometry for the noninvasive measurement of photosensitizer concentration in tissue during photodynamic therapy,” in Photodynamic Therapy: Mechanisms, (International Society for Optics and Photonics, 1989), pp. 115–122.

Pernuš, F.

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

Pfefer, T. J.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Pham, T. H.

Pifferi, A.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

Post, A. L.

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

Prabitha, V. G.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Prahl, S. A.

Preyer, N. W.

Qin, J.

J. Qin and R. Lu, “Measurement of the optical properties of fruits and vegetables using spatially resolved hyperspectral diffuse reflectance imaging technique,” Postharvest Biol. Technol. 49(3), 355–365 (2008).
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Quirk, C. J.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Rajaram, N.

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

Ramanujam, N.

B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
[Crossref]

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Reif, R.

Rema, P.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Richards-Kortum, R. R.

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003).
[Crossref]

Ross, R.

Ruchti, T. L.

S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

Saager, R.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Sampson, D. D.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Schmitt, J.

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
[Crossref]

Schwartz, E.

M. S. Patterson, E. Schwartz, and B. C. Wilson, “Quantitative reflectance spectrophotometry for the noninvasive measurement of photosensitizer concentration in tissue during photodynamic therapy,” in Photodynamic Therapy: Mechanisms, (International Society for Optics and Photonics, 1989), pp. 115–122.

Sebastian, P.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Shah, A.

Sharma, M.

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

Spott, T.

Sry, K.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Star, W.

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
[Crossref]

Star, W. M.

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
[Crossref]

Steiner, R.

Sterenborg, H.

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
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Sterenborg, H. J.

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

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V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Suchetha, S.

V. G. Prabitha, S. Suchetha, J. L. Jayanthi, K. V. Baiju, P. Rema, K. Anuraj, A. Mathews, P. Sebastian, and N. Subhash, “Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study,” Lasers Med. Sci. 31(1), 67–75 (2016).
[Crossref]

Sung, K.-B.

Svaasand, L. O.

Swartling, J.

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R. Ankri, H. Taitelbaum, and D. Fixler, “On Phantom experiments of the photon migration model in tissues,” The Open Optics Journal 5, 28–32 (2011).
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Tarnok, A.

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

Taroni, P.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

Ten Bosch, J.

Thennadil, S. N.

S. F. Malin, T. L. Ruchti, T. B. Blank, S. N. Thennadil, and S. L. Monfre, “Noninvasive prediction of glucose by near-infrared diffuse reflectance spectroscopy,” (Oxford University Press, 1999).

Thomas, S. S.

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

Torricelli, A.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

Tromberg, B. J.

Tseng, S.-H.

A. M. Grant, K. Sry, R. Saager, F. Ayers, T. J. Pfefer, K. M. Kelly, S.-H. Tseng, and A. J. Durkin, “Diffuse optical spectroscopy of melanoma-simulating silicone phantoms,” in Biomedical Applications of Light Scattering III, (International Society for Optics and Photonics, 2009), paper 718702.

Tseng, T.-Y.

Tunnell, J. W.

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

Turlach, B. A.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Utzinger, U.

U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003).
[Crossref]

Valentini, G.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “A solid tissue phantom for photon migration studies,” Phys. Med. Biol. 42(10), 1971–1979 (1997).
[Crossref]

Van Gemert, M.

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
[Crossref]

van Gemert, M. J.

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
[Crossref]

H. J. Van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. Van Gemert, “Light scattering in lntralipid-10% in the wavelength range of 400–1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991).
[Crossref]

Van Leeuwen, T. G.

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

van Marie, J.

Van Staveren, H. J.

Walker, E.

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
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Wall, R.

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
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Wang, L. V.

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B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

Wilke, J. A.

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

Wilson, B.

T. J. Farrell, M. S. Patterson, and B. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys. 19(4), 879–888 (1992).
[Crossref]

Wilson, B. C.

A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt. 35(13), 2304–2314 (1996).
[Crossref]

S. T. Flock, S. L. Jacques, B. C. Wilson, W. M. Star, and M. J. van Gemert, “Optical properties of Intralipid: a phantom medium for light propagation studies,” Lasers Surg. Med. 12, 510–519 (1992).
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B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990).
[Crossref]

M. S. Patterson, E. Schwartz, and B. C. Wilson, “Quantitative reflectance spectrophotometry for the noninvasive measurement of photosensitizer concentration in tissue during photodynamic therapy,” in Photodynamic Therapy: Mechanisms, (International Society for Optics and Photonics, 1989), pp. 115–122.

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D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
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Youssef, A.-B. M.

Yu, B.

B. Yu, A. Shah, V. K. Nagarajan, and D. G. Ferris, “Diffuse reflectance spectroscopy of epithelial tissue with a smart fiber-optic probe,” Biomed. Opt. Express 5(3), 675–689 (2014).
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B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
[Crossref]

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

Yu, J.-S.

Zhou, G.

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
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G. Zonios and A. Dimou, “Modeling diffuse reflectance from semi-infinite turbid media: application to the study of skin optical properties,” Opt. Express 14(19), 8661–8674 (2006).
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G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol. 117(6), 1452–1457 (2001).
[Crossref]

ACS Omega (1)

R. Ankri, R. Chakraborty, M. Motiei, and D. Fixler, “Three-Dimensional Highly Sensitive Diffusion Reflection-Based Imaging Method for the in Vivo Localization of Atherosclerosis Plaques Following Gold Nanorods Accumulation,” ACS Omega 3(6), 6134–6142 (2018).
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Appl. Opt. (9)

Y. S. Fawzi, A.-B. M. Youssef, M. H. El-Batanony, and Y. M. Kadah, “Determination of the optical properties of a two-layer tissue model by detecting photons migrating at progressively increasing depths,” Appl. Opt. 42(31), 6398–6411 (2003).
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J. Swartling, J. S. Dam, and S. Andersson-Engels, “Comparison of spatially and temporally resolved diffuse-reflectance measurement systems for determination of biomedical optical properties,” Appl. Opt. 42(22), 4612–4620 (2003).
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R. Reif, O. A’Amar, and I. J. Bigio, “Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media,” Appl. Opt. 46(29), 7317–7328 (2007).
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R. Groenhuis, H. A. Ferwerda, and J. Ten Bosch, “Scattering and absorption of turbid materials determined from reflection measurements. 1: Theory,” Appl. Opt. 22(16), 2456–2462 (1983).
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H. J. Van Staveren, C. J. Moes, J. van Marie, S. A. Prahl, and M. J. Van Gemert, “Light scattering in lntralipid-10% in the wavelength range of 400–1100 nm,” Appl. Opt. 30(31), 4507–4514 (1991).
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R. Groenhuis, J. Ten Bosch, and H. A. Ferwerda, “Scattering and absorption of turbid materials determined from reflection measurements. 2: Measuring method and calibration,” Appl. Opt. 22(16), 2463–2467 (1983).
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A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt. 35(13), 2304–2314 (1996).
[Crossref]

T. H. Pham, T. Spott, L. O. Svaasand, and B. J. Tromberg, “Quantifying the properties of two-layer turbid media with frequency-domain diffuse reflectance,” Appl. Opt. 39(25), 4733–4745 (2000).
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T. Papaioannou, N. W. Preyer, Q. Fang, A. Brightwell, M. Carnohan, G. Cottone, R. Ross, L. R. Jones, and L. Marcu, “Effects of fiber-optic probe design and probe-to-target distance on diffuse reflectance measurements of turbid media: an experimental and computational study at 337 nm,” Appl. Opt. 43(14), 2846–2860 (2004).
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Biomed. Opt. Express (2)

Brain Sci. (1)

M. Bhattacharya and A. Dutta, “Computational modeling of the photon transport, tissue heating, and cytochrome C oxidase absorption during transcranial near-infrared stimulation,” Brain Sci. 9(8), 179 (2019).
[Crossref]

IEEE J. Quantum Electron. (1)

B. C. Wilson and S. L. Jacques, “Optical reflectance and transmittance of tissues: principles and applications,” IEEE J. Quantum Electron. 26(12), 2186–2199 (1990).
[Crossref]

IEEE Photonics J. (1)

D. Fixler, H. Duadi, and I. Yariv, “Depth scattering characterization of multi-layer turbid media based on iterative multi-plane reflectance measurements,” IEEE Photonics J. 12(5), 1–13 (2020).
[Crossref]

IEEE Trans. Biomed. Eng. (1)

M. Van Gemert, S. L. Jacques, H. Sterenborg, and W. Star, “Skin optics,” IEEE Trans. Biomed. Eng. 36(12), 1146–1154 (1989).
[Crossref]

Int. J. Nanomed. (1)

R. Ankri, S. Melzer, A. Tarnok, and D. Fixler, “Detection of gold nanorods uptake by macrophages using scattering analyses combined with diffusion reflection measurements as a potential tool for in vivo atherosclerosis tracking,” Int. J. Nanomed. 10, 4437 (2015).
[Crossref]

J. Appl. Phys. (1)

J. Schmitt, G. Zhou, E. Walker, and R. Wall, “Multilayer model of photon diffusion in skin,” J. Appl. Phys. 7(11), 2141–2153 (1990).
[Crossref]

J. Biomed. Opt. (11)

A. L. Post, S. L. Jacques, H. J. Sterenborg, D. J. Faber, and T. G. Van Leeuwen, “Modeling subdiffusive light scattering by incorporating the tissue phase function and detector numerical aperture,” J. Biomed. Opt. 22(5), 050501 (2017).
[Crossref]

P. Naglič, F. Pernuš, B. Likar, and M. Bürmen, “Estimation of optical properties by spatially resolved reflectance spectroscopy in the subdiffusive regime,” J. Biomed. Opt. 21(9), 095003 (2016).
[Crossref]

R. Hennessy, W. Goth, M. Sharma, M. K. Markey, and J. W. Tunnell, “Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy,” J. Biomed. Opt. 19(10), 107002 (2014).
[Crossref]

U. Utzinger and R. R. Richards-Kortum, “Fiber optic probes for biomedical optical spectroscopy,” J. Biomed. Opt. 8(1), 121–148 (2003).
[Crossref]

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt. 10(6), 064020 (2005).
[Crossref]

D. Arifler, C. E. MacAulay, M. Follen, and R. R. Richards-Kortum, “Spatially resolved reflectance spectroscopy for diagnosis of cervical precancer: Monte Carlo modeling and comparison to clinical measurements,” J. Biomed. Opt. 11(6), 064027 (2006).
[Crossref]

T. J. Pfefer, L. S. Matchette, C. L. Bennett, J. A. Gall, J. A. Wilke, A. J. Durkin, and M. N. Ediger, “Reflectance-based determination of optical properties in highly attenuating tissue,” J. Biomed. Opt. 8(2), 206–216 (2003).
[Crossref]

N. Subhash, J. Mallia, S. S. Thomas, A. Mathews, P. Sebastian, and J. Madhaven, “Oral cancer detection using diffuse reflectance spectral ratio R540/R575 of oxygenated hemoglobin bands,” J. Biomed. Opt. 11(1), 014018 (2006).
[Crossref]

A. I. Mundo, G. J. Greening, M. J. Fahr, L. N. Hale, E. A. Bullard, N. Rajaram, and T. J. Muldoon, “Diffuse reflectance spectroscopy to monitor murine colorectal tumor progression and therapeutic response,” J. Biomed. Opt. 25(03), 1 (2020).
[Crossref]

B. Yu, H. L. Fu, and N. Ramanujam, “Instrument independent diffuse reflectance spectroscopy,” J. Biomed. Opt. 16(1), 011010 (2011).
[Crossref]

B. Yu, J. Y. Lo, T. F. Kuech, G. M. Palmer, J. E. Bender, and N. Ramanujam, “Cost-effective diffuse reflectance spectroscopy device for quantifying tissue absorption and scattering in vivo,” J. Biomed. Opt. 13(6), 060505 (2008).
[Crossref]

J. Biophotonics (1)

R. Ankri, H. Duadi, M. Motiei, and D. Fixler, “In-vivo Tumor detection using diffusion reflection measurements of targeted gold nanorods–a quantitative study,” J. Biophotonics 5(3), 263–273 (2012).
[Crossref]

J. Invest. Dermatol. (1)

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Figures (4)

Fig. 1.
Fig. 1. Schematic of fiber probe diffuse reflectance experimental setup: Tungsten halogen HL-2000-HP-FHSA (350–1000 nm) light source is connected to one of the 1-to-7 fan-out fibers of the optic bundle (denoted S), while the reaming six fibers are used for collection. The probe is placed on the phantom, and a FLAME-T-VIS-NIR-Spectrometer is connected to each of the output fibers to record the re-emitted signal.
Fig. 2.
Fig. 2. Process of extracting the reduced scattering coefficient of 1L phantoms. Six solid phantoms with varying Intralipid concentrations 0.75, 1, 1.25, 1.5, 1.75, 2% (upward-pointing triangle, circle, diamond, star, downward-pointing triangle, and hexagonal) were prepared. (a) Measured reflected light intensity from phantoms as a function of the distance ρ (at 500 nm) and linear fit (solid lines). (b) Calculated µs’ from the slope of the linear fits presented in (a) according to Eq. (4) as a function of wavelength. The solid line indicates the reduced scattering coefficients based on Mie theory [20]. The error bars indicate the standard deviations (< 0.12 mm−1) over the four sequential measurements from different positions on the sample.
Fig. 3.
Fig. 3. Extracted absorption coefficient as a function of wavelength and ink concentrations with constant scattering (1% Intralipid). The solid lines indicate the absorption coefficient values measured in a spectrophotometer. (a) Absorption coefficient as a function of the concentration of ink at different wavelengths (400 nm, 450 nm, 500 nm, 550 nm, 600 nm, 700 nm, 800 nm correspond to the upward-pointing triangle, star, diamond, square, hexagonal, downward-pointing triangle, circle). (b) Absorption coefficient as a function of wavelength (0, 1, 2, 3, 5, and 8×10−5 correspond to circle, star, upward-pointing triangle, square, hexagonal, diamond). Inset: the image of homogeneous single layer phantoms with constant scattering concentration and increasing absorption concentration, measured in the graph (standard deviations < 0.10 mm−1).
Fig. 4.
Fig. 4. Extracting the effective absorption coefficient and penetration depth from DR measurements of 2L phantoms (with a total thickness of 10 mm and constant scattering of 1% IL). (a) Extracted effective absorption coefficient as a function of wavelength with respect to the top-layer thickness of the sample (top layer thickness:1 mm, 2 mm, 3 mm, 4 mm, and 5 mm and control with a thickness of 10 mm (1% IL) correspond to the downward-pointing triangle, diamond, star, hexagonal, upward-pointing triangle, circle). (Standard deviation < 0.01 mm−1). (b) Calculated penetration depth according to Eq. (9) as a function of wavelength with respect to the sample thickness compared to 2δ according to the top layer (black solid) and bottom layer (dashed lines) optical coefficients. The solid and dashed lines are controls of the single-layer phantom, where the solid line represents a phantom with the properties of the top layer penetration depth and the dashed line represents the properties of the bottom layer. Inset: the image of phantoms with a varying top layer thickness (mm).

Equations (9)

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Φ ( r , t ) / c t + μ a Φ ( r , t ) D 2 Φ ( r , t ) = S ( r , t )
R ( ρ ) = ( C 1 ρ m ) exp μ e f f . ρ
μ e f f = μ a D = 3 μ a ( μ a + μ s )
ln ( R ( ρ ) . ρ m ) = C 2 μ e f f . ρ
μ e f f 3 μ a μ s
δ = 1 μ e f f
μ a e f f = μ a _ I L T T + B + μ a _ I n k + I L B T + B
B = T ( μ a _ I L μ a e f f ) ( μ a e f f μ a _ I n k + I L )
T + B δ