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2022-10-13
Research on Sparse Imaging Method of Electrical Impedance Tomography Based on DK-SVD
By
Qi Wang,

    Dr. Qi Wang

    Tiangong University

    China

    Homepage

Xin Ding,

    Dr. Xin Ding

    School of Electronic and Information Engineering

    Tiangong University

    China

    Homepage

Ming Ma,

    Dr. Ming Ma

    School of Life Science

    Tiangong University

    China

    Homepage

Xiuyan Li,

    Dr. Xiuyan Li

    Tiangong University

    China

    Homepage

Xiaojie Duan,

    Dr. Xiaojie Duan

    Tiangong University

    China

    Homepage

Jianming Wang

    Professor Jianming Wang

    School of Computing

    Tiangong University

    China

    Homepage

Progress In Electromagnetics Research M, Vol. 114, 13-25, 2022
doi:10.2528/PIERM22071604 | Google Scholar

Abstract
As a noninvasive imaging technique for the interior of objects, Electrical Impedance Tomography (EIT) is widely used in many fields of biomedicine. Sparse reconstruction algorithms have made major breakthroughs in the field of image reconstruction in recent years. The K-SVD algorithm is an adaptive dictionary signal sparse representation algorithm, which could improve the reconstruction accuracy. However, the parameters in the K-SVD algorithm are fixed, which cannot match all the measurement data of EIT very well. Moreover, the K-SVD algorithm adopts a greedy algorithm in the sparse coding stage, which has high computational complexity. In this study, an electrical impedance sparse imaging method based on DK-SVD (deep k-singular value decomposition) was designed. It provides the corresponding optimal model parameters for each set of measurement data through the method of multi-layer perceptron (MLP) network training, thereby improving the imaging quality. At the same time, the iterative soft threshold algorithm (ISTA) is used in the sparse coding stage to improve the convergence speed. The reconstruction results show that compared with the K-SVD algorithm and Total Variation (TV) algorithm, the reconstruction error of the DK-SVD method is smaller, and the irregular and sharp inclusions can be accurately reconstructed. Image artifacts are also greatly reduced.
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Citation
Qi Wang, Xin Ding, Ming Ma, Xiuyan Li, Xiaojie Duan, and Jianming Wang, "Research on Sparse Imaging Method of Electrical Impedance Tomography Based on DK-SVD," Progress In Electromagnetics Research M, Vol. 114, 13-25, 2022.
doi:10.2528/PIERM22071604
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