Acta Optica Sinica, Volume. 41, Issue 11, 1117001(2021)

Parameters Inversion Algorithm of Biological Tissues Based on a Neural Network Model

Ge Xu, Liquan Dong*, Lingqin Kong, Yuejin Zhao, Ming Liu, Mei Hui, Xiaohua Liu, Falong Wang, and Jing Yuan
Author Affiliations
  • Beijing Key Laboratory for Precision Optoelectronic Measurement Instrument and Technology, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
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    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.

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    Ge Xu, Liquan Dong, Lingqin Kong, Yuejin Zhao, Ming Liu, Mei Hui, Xiaohua Liu, Falong Wang, Jing Yuan. Parameters Inversion Algorithm of Biological Tissues Based on a Neural Network Model[J]. Acta Optica Sinica, 2021, 41(11): 1117001

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    Paper Information

    Category: Medical Optics and Biotechnology

    Received: Sep. 27, 2020

    Accepted: Jan. 8, 2021

    Published Online: Jun. 7, 2021

    The Author Email: Dong Liquan (kylind@bit.edu.cn)

    DOI:10.3788/AOS202141.1117001

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