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| Study on the Electrical Impedance Block Sparse Imaging Method of Deep Learning Based on DK-SVD |
| WANG Qi1,YANG Yuhan1,LI Xiuyan1,DUAN Xiaojie1,WANG Jianming2,SUN Yukuan2,FENG Hui3 |
1. Electronic and Information Engineering College,Tianjin Polytechnic University,Tianjin 300387,China
2. Computer Science College, Tianjin Polytechnic University, Tianjin 300387,China
3. Jiangning Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu 211100, China |
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Abstract Aiming at the ill-posedness and nonlinearity of electrical impedance tomography inverse problem, a DK-SVD-based block sparse image reconstruction method is proposed.The multi-layer perceptron is introduced to finetune optimal model parameters for measurement data considering the complexity of datasets and improve the image quality.The iterative shrinkage threshold algorithm is used to accelerate convergence in the sparse coding stage.The simulation results show that the structural similarity of the reconstructed image by DK-SVD algorithm can reach more than 0.95, the error can be controlled at about 0.1, and the average reconstruction speed is 0.034s, which effectively improves the quality and efficiency of electrical impedance tomography, and further experiments prove that the algorithm has good noise robustness and practical application value.
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Received: 18 August 2023
Published: 26 September 2024
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2024, Vol. 45 
