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Abstract #1189

Improved CS-MRI using Hybrid Plug-and-Play Priors based Fast Composite Splitting Algorithm

Qingyong Zhu1, Jing Cheng2, Zhuo-Xu Cui1, and Dong Liang1,2
1Research Center for Medical AI, SIAT, Chinese Academy of Sciences, Shenzhen, China, 2Paul C. Lauterbur Research Center for Biomedical Imaging, SIAT, Chinese Academy of Sciences, Shenzhen, China

The Plug-and-Play prior (PnP) is also known as denoising prior which has been successfully utilized in non-linear imaging problems. The paper presents a hybrid PnP which is incorporated into the fast composite splitting algorithm (FCSA) for compressed sensing magnetic resonance imaging (CS-MRI). The advantage of the hybrid PnP over generic PnP such as BM3D is that it can further remove artifacts and preserve adaptively fine structures in CS-MRI reconstruction. Experimental results and performance comparisons with generic PnP-FISTA show the superiority of the proposed approach even for high acceleration factor.

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