Diffuse optical tomography image reconstruction based on graph convolution network

Linxuan Su; Chengpu Wei; Zhe Li; Zhonghua Sun; Kebin Jia; Jinchao Feng

doi:10.1117/12.2682860

18 July 2023 Diffuse optical tomography image reconstruction based on graph convolution network

Linxuan Su, Chengpu Wei, Zhe Li, Zhonghua Sun, Kebin Jia, Jinchao Feng

Proceedings Volume 12745, Sixteenth International Conference on Photonics and Imaging in Biology and Medicine (PIBM 2023); 127450Z (2023) https://doi.org/10.1117/12.2682860
Event: Sixteenth International Conference on Photonics and Imaging in Biology and Medicine (PIBM 2023), 2023, Haikou, China

Abstract

Diffuse Optical Tomography (DOT) is a promising noninvasive imaging method which quantifies optical parameters to achieve functional characteristics of biological tissues. Since boundary measurements are limited and the light propagation in biological tissues is highly diffusive, DOT image reconstruction is ill-posed and ill-conditioned. Traditional iteration-based regularization methods, such as Tikhonov regularization, tend to produce low-quality images with severe artifacts. Deep learning reconstruction methods based on convolutional neural networks may ignore the structure information of finite element mesh during feature extraction and cause the loss of spatial features. In order to overcome these problems, we propose a novel neural network based on graph convolution to improve the quality of reconstructed DOT images. Graph convolution can make full use of the spatial structure information of finite element mesh and deal with the potential correlation between optical features effectively. To verify the performance of the proposed algorithm, simulation experiments were performed. We also compared the proposed algorithm with Tikhonov regularization method and deep learning method based on convolutional neural network. Experimental results show that proposed algorithm obtains better reconstruction results in terms of ABE, MSE, PSNR and SSIM.

Citation Download Citation

Linxuan Su, Chengpu Wei, Zhe Li, Zhonghua Sun, Kebin Jia, and Jinchao Feng "Diffuse optical tomography image reconstruction based on graph convolution network", Proc. SPIE 12745, Sixteenth International Conference on Photonics and Imaging in Biology and Medicine (PIBM 2023), 127450Z (18 July 2023); https://doi.org/10.1117/12.2682860

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KEYWORDS

Image restoration

Reconstruction algorithms

Convolution

Matrices

Deep learning

Diffuse optical tomography

Image quality

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