基于神经网络模型的生物组织参数反演算法

During the inversion of optical parameters of biological tissues, the measurement accuracy is low and the in vivo measurement is difficult. Therefore, a neural network model to invert the optical parameters of biological tissues was proposed in this paper. In this method, the diffuse reflectance R(r) at different detection distances r from the Monte Carlo algorithm is used as the input, and the absorption coefficient and scattering coefficient are taken as the output. The absorption coefficient and scattering coefficient retrieved by the neural network algorithm are compared with those by the Monte Carlo algorithm. The simulation results show that with the diffuse reflectance at r=0.1 cm and r=0.3 cm as the input, the mean absolute errors are 0.003 and 1.574, respectively for the absorption coefficient and scattering coefficient retrieved by the neural network algorithm, and the consistency coefficient of determination R² can reach 0.9997 and 0.9915, respectively. The biological tissue parameters retrieved by the neural network model agree well with the absorption coefficient and scattering coefficient obtained by the Monte Carlo algorithm. The neural network model has the advantages of high inversion accuracy and simple operation, which provides a new method for the in vivo measurement of optical parameters of biological tissues.