[1] Xu Kexin, Gao Feng, Zhao Huijuan. Biomedical Photonics [M]. Beijing: Science Press, 2007. 11-22.
[2] C Zhu, Quan Liu. Review of Monte Carlo modeling of light transport in tissues [J]. J Biomed Opt, 2013, 18(5): 050902.
[3] M Larsson, H Nilsson, T Strmberg. 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 [J]. Appl Opt, 2003, 42(1): 124-134.
[4] Q Z Wang, K Shastri, T J Pfefer. Experimental and theoretical evaluation of a fiber-optic approach for optical property measurement in layered epithelial tissue [J]. Appl Opt, 2010, 49(28): 5309-5320.
[5] Q Z Wang, A Agrawal, N S Wang, et al.. Condensed Monte Carlo modeling of reflectance from biological tissue with a single illumination-detection fiber [J]. IEEE J Sel Top Quantum Electron, 2010, 16(3): 627-634.
[6] L S Zhang, Z Z Wang, M Y Zhou. Determination of the optical coefficients of biological tissue by neural network [J]. J Modern Opt, 2010, 57(13): 1163-1170.
[7] M H Niemz. Laser-Tissue Interactions Fundamentals and Applications [M]. Zhang Zhenxi Transl.. Beijing: Science Press, 2005. 24-32.
[8] Li Chenxi, Zhao Huijuan, Zheng Jiaxiang, et al.. Design and property of depth-selective fiber-optical probes applied in diffuse reflection measurement [J]. Acta Optica Sinica, 2012, 32(7): 0717001.
[10] T J Pfefer, L S Matchette, C L Bennett, et al.. Reflectance-based determination of optical properties in highly attenuating tissue [J]. J Biomed Opt, 2003, 8(2): 206-215.
[11] Q Z Wang, D Le, J Ramella-Roman, et al.. Broadband ultraviolet-visible optical property measurement in layered turbid media [J]. Biomed Opt Express, 2012, 3(6): 1226-1240.
[12] M Jger, F Foschum, A Kienle. Application of multiple artificial neural networks for the determination of the optical properties of turbid media [J]. J Biomed Opt, 2013, 18(5): 057005.
[13] G M Palmer, N Ramanujam. Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms [J]. Appl Opt, 2006, 45(5): 1062-1071.
[14] T A Erickson, A Mazhar, D Cuccia, et al.. Lookup-table method for imaging optical properties with structured illumination beyond the diffusion theory regime [J]. J Biomed Opt, 2010, 15(3): 036013.
[15] R Zhang, W Verkruysse, B Choi, et al.. Determination of human skin optical properties from spectrophotometric measurements based on optimization by genetic algorithms [J]. J Biomed Opt, 2005, 10(2): 024030.
[16] S A Prahl, M Keijzer, S L Jacques, et al.. A Monte Carlo model of light propagation in tissue [J]. SPIE Institute Series, 1989, IS5: 102-111.
[17] L H Wang, S L Jacques, L Q Zheng. MCML: Monte Carlo modeling of light transport in multi-layered tissues [J]. Computer Methods Programs in Biomedicine, 1995, 47(2): 131-146.
[18] E Alerstam, T Svensson, S Andersson-Engels. Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration [J]. J Biomed Opt, 2008, 13(6): 060504.
[19] E Alerstam, W C Y Lo, T D Han, et al.. Next-generation acceleration and code optimization for light transport in turbid media using GPUs [J]. Biomed Opt Express, 2010, 1(2): 658-675.
[20] F H Cai, S L He. Using graphics processing units to accelerate perturbation Monte Carlo simulation in a turbid medium [J]. J Biomed Opt, 2012, 17(4): 040502.
[21] F Herrera, M Lozano, J L Verdegay. Tackling real-coded genetic algorithms: operators and tools for behavioural analysis [J]. Artificial Intelligence Review, 1998, 12(4): 265-319.
[22] V Tuchin. Tissue Optics: Light Scattering Methods and Instruments for Medical Diagnosis, Second Edition [M]. Washington: SPIE Press, 2007. 145-191.