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Abstract #2703

Three Dimensional Restoration of Cardiac Magnetic Resonance Diffusion Weighted Images Based on Sparse Denoising

Lijun Bao1, Wanyu Liu2, Changwei Hu1, Xiaobo Qu3, Shuhui Cai1, Zhong Chen1

1Department of Physics, Xiamen University, Xiamen, Fujian, China, People's Republic of; 2Departments of Automatic Measurement & Control, Harbin Institute of Technology, Harbin, China, People's Republic of; 3Department of Communication Engineering, Xiamen University, Xiamen, Fujian, China, People's Republic of


There are spatial correlations between adjacent layers in cardiac DWI sequence due to the organ consistency, and each DWI contains repetitive structures. Therefore, sparsity could arise from self-similarity of cardiac DWIs. A 3D restoration method based on structure adaptive sparse denoising (SAP-SPDN) is proposed. Experimental results demonstrate that SAP-SPDN algorithm has a good performance in denoising images with high structural redundancy. It can achieve a trade-off between image contrast and smoothness in denoising.

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