本研究中提出了一套掃描型非接觸式漫反射光譜量測系統，本系統的量測光譜波段為500-1000nm。利用微機電反射鏡(Microelectromechanical System Mirror, MEMS Mirror)達到快速調控光源與偵測器之距離，並配合電控可變焦透鏡(Tunable Lens)同步調整偵測點聚焦位置，接收待測物表面之漫反射光訊號，達到一維的掃描式量測架構。最後，結合蒙地卡羅法(Monte Carlo Method)及人工類神經網路(Artificial Neural Network, ANN)，用於獲取淺層皮膚組織之光學特性並擬合出生理參數。
在本研究中，以蒙地卡羅模擬光源斜向入射與偵測器斜向收光兩種模型的角度限制與誤差，驗證本研究團隊已開發之接觸式漫反射光譜系統之人工類神經網路適用於非接觸是漫反射光譜系統，並以量測仿體驗證光源端與偵測端兩種非接觸式漫反射光譜系統的可行性與準確性。其次，結合上述兩套系統，再次以量測仿體驗證完整漫反射光譜系統之可行性與準確性，並探討若用於人體量測時，因人體組織曲面對系統量測距離造成的影響。最後，本研究挑選了三位膚色差異明顯的自願受測者，在正常與靜脈閉鎖兩種狀態下，進行一維的掃描式量測，比較其組織血氧濃度、血紅素與黑色素等色團之變化。

In this study, we proposed a non-contact scanning diffuse reflectance spectroscopy measurement system. This system uses the supercontinuum laser, which is a broadband and steady-state light. Use Microelectromechanical System Mirror (MEMS Mirror) as a scanning mechanism to quickly switch source and detector separations and change measurement position. Simultaneously, collect diffuse reflectance spectroscopy signal and match focal length by tunable lens. Achieve one-dimensional scanning measurement structure. The Algorithm combine Monte Carlo Method (MCML) and Artificial Neural Network (ANN) to obtain optical properties from superficial skin tissue. Second, we demonstrate the system feasibility and accuracy by phantom. Finally, we select three volunteers, whom skin colour is differences, significantly. Compare those tissue oxygen concentration, oxyhemoglobin, melanin, and other chromophores in vivo.

[1]. Lee, J.Y., et al., Intraoperative Near-Infrared Optical Imaging Can Localize Gadolinium-Enhancing Gliomas During Surgery. Neurosurgery, 2016. 79(6): p. 856-871.
[2]. Huang, D., et al., Optical coherence tomography. Science, 1991. 254(5035): p. 1178-81.
[3]. Xi, L., et al., Photoacoustic imaging based on MEMS mirror scanning. Biomed Opt Express, 2010. 1(5): p. 1278-1283.
[4]. Doornbos, R.M., et al., The determination of in vivo human tissue optical properties and absolute chromophore concentrations using spatially resolved steady-state diffuse reflectance spectroscopy. Phys Med Biol, 1999. 44(4): p. 967-81.
[5]. Tseng, S.H., A. Grant, and A.J. Durkin, In vivo determination of skin near-infrared optical properties using diffuse optical spectroscopy. J Biomed Opt, 2008. 13(1): p. 014016.
[6]. Zonios, G., 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, 2001. 117(6): p. 1452-7.
[7]. Tseng, S.H., et al., Chromophore concentrations, absorption and scattering properties of human skin in-vivo. Opt Express, 2009. 17(17): p. 14599-617.
[8]. Tseng, S.H., et al., Investigation of a probe design for facilitating the uses of the standard photon diffusion equation at short source-detector separations: Monte Carlo simulations. J Biomed Opt, 2009. 14(5): p. 054043.
[9]. Tseng, S.H., et al., Noninvasive evaluation of collagen and hemoglobin contents and scattering property of in vivo keloid scars and normal skin using diffuse reflectance spectroscopy: pilot study. J Biomed Opt, 2012. 17(7): p. 077005.
[10]. Volynskaya, Z., et al., Diagnosing breast cancer using diffuse reflectance spectroscopy and intrinsic fluorescence spectroscopy. J Biomed Opt, 2008. 13(2): p. 024012.
[11]. Durduran, T., et al., Diffuse optical measurement of blood flow, blood oxygenation, and metabolism in a human brain during sensorimotor cortex activation. Opt Lett, 2004. 29(15): p. 1766-8.
[12]. Zhou, C., et al., Diffuse optical monitoring of hemodynamic changes in piglet brain with closed head injury. J Biomed Opt, 2009. 14(3): p. 034015.
[13]. Yu, G., et al., Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies. J Biomed Opt, 2005. 10(2): p. 024027.
[14]. Tseng, S.H., et al., Quantitative spectroscopy of superficial turbid media. Opt Lett, 2005. 30(23): p. 3165-7.
[15]. Reif, R., et al., Analysis of changes in reflectance measurements on biological tissues subjected to different probe pressures. J Biomed Opt, 2008. 13(1): p. 010502.
[16]. Popov, A.P., A.V. Bykov, and I.V. Meglinski, Influence of probe pressure on diffuse reflectance spectra of human skin measured in vivo. J Biomed Opt, 2017. 22(11): p. 1-4.
[17]. Cugmas, B., et al., Pressure-induced near infrared spectra response as a valuable source of information for soft tissue classification. J Biomed Opt, 2013. 18(4): p. 047002.
[18]. Andree, S., et al., Evaluation of a novel noncontact spectrally and spatially resolved reflectance setup with continuously variable source-detector separation using silicone phantoms. J Biomed Opt, 2010. 15(6): p. 067009.
[19]. Bish, S.F., et al., Development of a noncontact diffuse optical spectroscopy probe for measuring tissue optical properties. J Biomed Opt, 2011. 16(12): p. 120505.
[20]. Bish, S.F., et al., Handheld Diffuse Reflectance Spectral Imaging (DRSi) for in-vivo characterization of skin. Biomed Opt Express, 2014. 5(2): p. 573-86.
[21]. Sorgato, V., et al., ACA-Pro: calibration protocol for quantitative diffuse reflectance spectroscopy. Validation on contact and noncontact probe- and CCD-based systems. J Biomed Opt, 2016. 21(6): p. 65003.
[22]. Alerstam, E., T. Svensson, and S. Andersson-Engels, Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration. J Biomed Opt, 2008. 13(6): p. 060504.
[23]. Banerjee, S. and S.K. Sharma, Use of Monte Carlo simulations for propagation of light in biomedical tissues. Appl Opt, 2010. 49(22): p. 4152-9.
[24]. Wang, L., S.L. Jacques, and L. Zheng, MCML--Monte Carlo modeling of light transport in multi-layered tissues. Comput Methods Programs Biomed, 1995. 47(2): p. 131-46.
[25]. Chen, Y.W. and S.H. Tseng, Efficient construction of robust artificial neural networks for accurate determination of superficial sample optical properties. Biomed Opt Express, 2015. 6(3): p. 747-60.
[26]. Farrell, T.J., 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, 1992. 37(12): p. 2281-6.
[27]. Bydlon, T.M., et al., Chromophore based analyses of steady-state diffuse reflectance spectroscopy: current status and perspectives for clinical adoption. J Biophotonics, 2015. 8(1-2): p. 9-24.
[28]. Stamatas, G.N. and N. Kollias, Blood stasis contributions to the perception of skin pigmentation. J Biomed Opt, 2004. 9(2): p. 315-22.