Artificial neural network method for determining optical properties from double-integrating-spheres measurements
Chinese Optics Letters, Vol. 8, Issue 2, pp. 173-176 (2010)
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Abstract
Accurate measurement of the optical properties of biological tissue is very important for optical diagnosis and therapeutics. An artificial neural network (ANN)-based inverse reconstruction method is introduced to determine the optical properties of turbid media, which is based on the reflectance (R) and transmittance (T) of a thin sample measured by a double-integrating-spheres system. The accuracy and robustness of the method has been validated, and the results show that the root mean square errors (RMSEs) of the absorption coefficient \mu a and scattering coefficient \mu' s reconstruction are less than 0.01 cm-1 and 0.02 cm-1, respectively. The algorithm is not only very accurate in the case of a lower albedo (~0.33), but also very robust to the noise of R and T especially for the \mu' s reconstruction.
© 2010 Chinese Optics Letters
OCIS Codes
(120.3150) Instrumentation, measurement, and metrology : Integrating spheres
(290.5820) Scattering : Scattering measurements
(290.7050) Scattering : Turbid media
(300.1030) Spectroscopy : Absorption
Citation
Chenxi Li, Huijuan Zhao, Qiuyin Wang, and Kexin Xu, "Artificial neural network method for determining optical properties from double-integrating-spheres measurements," Chin. Opt. Lett. 8, 173-176 (2010)
http://www.opticsinfobase.org/col/abstract.cfm?URI=col-8-2-173
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