Boosting of Half-Quadratic Splitting Algorithm for Undersampled Brain MRI Reconstruction
Qingyong Zhu1, Jing Cheng2, Zhuo-Xu Cui1, Yuanyuan Liu3, Yanjie Zhu2, and Dong Liang1
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, 3National Innovation Center for Advanced Medical Devices, Shenzhen, China, Shenzhen, China
The existing accelerated MRI methods have the limitations such as fine-structure loss in the cases of high reduction factors or noisy measurements. This work presents a novel mutual-structure filtering based half-quadratic splitting algorithm for accurate undersampled brain MRI reconstruction. Experimental results on in-vivo images have shown that the proposed approach has a superior ability to capture meaningful details compared with other state-of-the-art reference guided reconstruction technologies.
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