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19 December 2018 Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography
Jinchao Feng, Qiuwan Sun, Zhe Li, Zhonghua Sun, Kebin Jia
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Journal of Biomedical Optics, Vol. 24, Issue 5, 051407 (December 2018). https://doi.org/10.1117/1.JBO.24.5.051407
Abstract
Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of providing functional characteristics of biological tissue by quantifying optical parameters. The DOT image reconstruction is ill-posed and ill-conditioned, due to the highly diffusive nature of light propagation in biological tissues and limited boundary measurements. The widely used regularization technique for DOT image reconstruction is Tikhonov regularization, which tends to yield oversmoothed and low-quality images containing severe artifacts. It is necessary to accurately choose a regularization parameter for Tikhonov regularization. To overcome these limitations, we develop a noniterative reconstruction method, whereby optical properties are recovered based on a back-propagation neural network (BPNN). We train the parameters of BPNN before DOT image reconstruction based on a set of training data. DOT image reconstruction is achieved by implementing a single evaluation of the trained network. To demonstrate the performance of the proposed algorithm, we compare with the conventional Tikhonov regularization-based reconstruction method. The experimental results demonstrate that image quality and quantitative accuracy of reconstructed optical properties are significantly improved with the proposed algorithm.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Jinchao Feng, Qiuwan Sun, Zhe Li, Zhonghua Sun, and Kebin Jia "Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography," Journal of Biomedical Optics 24(5), 051407 (19 December 2018). https://doi.org/10.1117/1.JBO.24.5.051407
Received: 13 August 2018; Accepted: 30 November 2018; Published: 19 December 2018
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Cited by 64 scholarly publications and 1 patent.
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KEYWORDS
Reconstruction algorithms
Neural networks
Absorption
Diffuse optical tomography
Image restoration
Image quality
Neurons
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