Artificial neural network method for determining optical properties from double-integrating-spheres measurements

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