本研究中，我們提出以FDPM系統量測SDS=1mm之人體皮膚，為了改善傳統光子傳播模型的缺點 ( Monte Carlo model:光子傳播演算時間過久，diffusion theory:高反照率→縮減散射係數≫吸收係數，且光子在組織中的平均自由路徑長度≫1/(縮減散射係數+吸收係數))，將透過GPU-MCML建立大量的database，並經由類神經建立吸收係數、縮減散射係數隨頻率對應的振幅與相位延遲量的光子傳播模型，取代傳統Monte Carlo model與diffusion theory，本論文題出之方法比起Monte Carlo model其優勢為可快速模擬吸收係數、縮減散射係數隨頻率對應的振幅與相位延遲量，比起diffusion theory其優勢將不受到行走路徑的影響，且可應用於大範圍吸收係數、縮減散射係數組合。
以模擬實驗而言，Monte Carlo model為光子傳播模型的黃金標準，GPU-MCML在振幅方面與MCML的誤差為4%，相位延遲的誤差為6%，而diffusion theory在振幅方面與MCML的誤差為30%，相位延遲的誤差為17%。我們也以已知光學性質的均質假體驗證類神經模擬的可行性，因此就SDS=1mm的距離，類神經模型有其絕對的優勢。
以人體皮膚量測而言，我們以3個受測者為例，並個別量測三個部位，分別是手指、前手臂內側、前手臂外側，經由類神經傳播模型推算出吸收係數、縮減散射係數，由三個波長下的吸收係數進行chromophore fitting，分析組織的血氧飽和濃度，達到量化組織色團濃度的目的。
簡而言之，類神經模型是快速且應用範圍廣泛的。而以本研究中訓練的人體皮膚範為的吸收係數、縮減散射係數其最大偵測深度約為1.6mm。透過SDS=1mm之類神經光子傳播模型的建立與驗證可行性下，本研究將可以精確的計算出淺層皮膚的光學性質。

In this study, we propose a method to measure human skin with SDS = 1mm by FDPM system. In order to improve the shortcomings of traditional photon propagation model, we established a new photon propagation model which combined the GPU-MCML and ANN method to derive the sample absorption coefficient、reduced scattering coefficient corresponding to the amplitude and phase delay with the frequency. The new model can substitute traditional Monte Carlo model and standard diffusion equation which have some using limitation.
In simulation, Monte Carlo is considered as a gold standard model of photon propagation. However it consumes lots of time to do the simulation. Compared with Monte Carlo, the percent deviation of amplitude and phase which simulated by artificial neural networks are about 4% and 6%, respectively. In the other hand, comparing with Monte Carlo, the percent deviation of amplitude and phase which simulated by standard diffusion equation are about 30% and 17%, respectively. Therefore compared with diffusion equation the new model with a 1mm source to detector separation indeed has its absolute advantage. We also use the homogeneous phantom which optical properties is known to confirm the feasibility of the artificial neural networks model.
In experience,we measured three position of three healthy adults, including the finger, the inner forearm and outer forearm with the artificial neural networks model extrapolated absorption coefficient、reduced scattering coefficient with three wavelengths. And then we put the absorption coefficient into the chromophore fitting to quantify the chromophore concentrations of tissue and StO2.
In conclusion, our new artificial neural networks model has better efficiency and wider applied range than other traditional model, which can accurately calculate the optical properties of the superficial skin tissue.

[1] I. Riemann, P. Fischer, M. Kaatz, T. W. Fischer, P. Elsner, E. Dimitrov, et al., "Optical tomography of pigmented human skin biopsies," 2004, pp. 24-34.
[2] Q. Liu and N. Ramanujam, "Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra," Appl Opt, vol. 45, pp. 4776-90, Jul 1 2006.
[3] H. Roehrig, X. Gu, and J. Fan, "Physical evaluation of color and monochrome medical displays using an imaging colorimeter," 2013, pp. 86731T-86731T-8.
[4] 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, vol. 35, pp. 2304-14, May 1 1996.
[5] M. Larsson, H. Nilsson, and T. Stromberg, "In vivo determination of local skin optical properties and photon path length by use of spatially resolved diffuse reflectance with applications in laser Doppler flowmetry," Appl Opt, vol. 42, pp. 124-34, Jan 1 2003.
[6] R. Bays, G. Wagnieres, D. Robert, D. Braichotte, J. F. Savary, P. Monnier, et al., "Clinical determination of tissue optical properties by endoscopic spatially resolved reflectometry," Appl Opt, vol. 35, pp. 1756-66, Apr 1 1996.
[7] K. B. Sung, K. W. Shih, F. W. Hsu, H. P. Hsieh, M. J. Chuang, Y. H. Hsiao, et al., "Accurate extraction of optical properties and top layer thickness of two-layered mucosal tissue phantoms from spatially resolved reflectance spectra," J Biomed Opt, vol. 19, p. 77002, 2014.
[8] P. G. Buettner, U. Leiter, T. K. Eigentler, and C. Garbe, "Development of prognostic factors and survival in cutaneous melanoma over 25 years: An analysis of the Central Malignant Melanoma Registry of the German Dermatological Society," Cancer, vol. 103, pp. 616-24, Feb 1 2005.
[9] A. Breslow, "Thickness, cross-sectional areas and depth of invasion in the prognosis of cutaneous melanoma," Ann Surg, vol. 172, pp. 902-8, Nov 1970.
[10] H. Y. Lin, N. Cheng, S. H. Tseng, and M. C. Chan, "Higher-order modulations of fs laser pulses for GHz frequency domain photon migration system," Opt Express, vol. 22, pp. 3950-8, Feb 24 2014.
[11] 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, vol. 39, pp. 4733-45, Sep 1 2000.

[12] H. Arimoto, M. Egawa, and Y. Yamada, "Depth profile of diffuse reflectance near-infrared spectroscopy for measurement of water content in skin," Skin Res Technol, vol. 11, pp. 27-35, Feb 2005.
[13] 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, vol. 19, p. 107002, 2014.
[14] S. H. Tseng, A. Grant, and A. J. Durkin, "In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy," J Biomed Opt, vol. 13, p. 014016, Jan-Feb 2008.
[15] K. M. Yoo, F. Liu, and R. R. Alfano, "When does the diffusion approximation fail to describe photon transport in random media?," Phys Rev Lett, vol. 64, pp. 2647-2650, May 28 1990.
[16] F. Martelli, M. Bassani, L. Alianelli, L. Zangheri, and G. Zaccanti, "Accuracy of the diffusion equation to describe photon migration through an infinite medium: numerical and experimental investigation," Phys Med Biol, vol. 45, pp. 1359-73, May 2000.
[17] A. E. Cerussi, D. Jakubowski, N. Shah, F. Bevilacqua, R. Lanning, A. J. Berger, et al., "Spectroscopy enhances the information content of optical mammography," J Biomed Opt, vol. 7, pp. 60-71, Jan 2002.
[18] G. Themelis, H. D'Arceuil, S. G. Diamond, S. Thaker, T. J. Huppert, D. A. Boas, et al., "Near-infrared spectroscopy measurement of the pulsatile component of cerebral blood flow and volume from arterial oscillations," J Biomed Opt, vol. 12, p. 014033, Jan-Feb 2007.
[19] D. Arifler, R. A. Schwarz, S. K. Chang, and R. Richards-Kortum, "Reflectance spectroscopy for diagnosis of epithelial precancer: model-based analysis of fiber-optic probe designs to resolve spectral information from epithelium and stroma," Appl Opt, vol. 44, pp. 4291-305, Jul 10 2005.
[20] T. J. Pfefer, A. Agrawal, and R. A. Drezek, "Oblique-incidence illumination and collection for depth-selective fluorescence spectroscopy," J Biomed Opt, vol. 10, p. 44016, Jul-Aug 2005.
[21] S. H. Tseng, P. Bargo, A. Durkin, and N. Kollias, "Chromophore concentrations, absorption and scattering properties of human skin in-vivo," Opt Express, vol. 17, pp. 14599-617, Aug 17 2009.
[22] E. Alerstam, T. Svensson, and S. Andersson-Engels, "Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration," J Biomed Opt, vol. 13, p. 060504, Nov-Dec 2008.

[23] M. Jager, F. Foschum, and A. Kienle, "Application of multiple artificial neural networks for the determination of the optical properties of turbid media," J Biomed Opt, vol. 18, p. 57005, May 2013.
[24] T. J. Farrell, B. C. Wilson, and M. S. Patterson, "The use of a neural network to determine tissue optical properties from spatially resolved diffuse reflectance measurements," Phys Med Biol, vol. 37, pp. 2281-6, Dec 1992.
[25] F. Bevilacqua, A. J. Berger, A. E. Cerussi, D. Jakubowski, and B. J. Tromberg, "Broadband absorption spectroscopy in turbid media by combined frequency-domain and steady-state methods," Appl Opt, vol. 39, pp. 6498-507, Dec 1 2000.
[26] V. Podrazky and V. Sedmerova, "Densities of collagen dehydrated by some organic solvents," Experientia, vol. 22, p. 792, Dec 15 1966.
[27] P. Taroni, A. Bassi, D. Comelli, A. Farina, R. Cubeddu, and A. Pifferi, "Diffuse optical spectroscopy of breast tissue extended to 1100 nm," J Biomed Opt, vol. 14, p. 054030, Sep-Oct 2009.
[28] L. Wang, S. L. Jacques, and L. Zheng, "MCML--Monte Carlo modeling of light transport in multi-layered tissues," Comput Methods Programs Biomed, vol. 47, pp. 131-46, Jul 1995.
[29] M. Testorf, U. Osterberg, B. Pogue, and K. Paulsen, "Sampling of time- and frequency-domain signals in monte carlo simulations of photon migration," Appl Opt, vol. 38, pp. 236-45, Jan 1 1999.
[30] I. V. Yaroslavsky, A. N. Yaroslavsky, V. V. Tuchin, and H. J. Schwarzmaier, "Effect of the scattering delay on time-dependent photon migration in turbid media," vol. 36, pp. 6529-6538--, 1997.