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Abstract #1760

Intelligent Incorporation of AI with Model Constraints for MRI Acceleration

Renkuan Zhai1, Xiaoqian Huang2, Yawei Zhao1, Meiling Ji1, Xuyang Lv2, Mengyao Qian1, Shu Liao2, and Guobin Li1
1United Imaging Healthcare, Shanghai, China, 2United Imaging Intelligence, Shanghai, China

The advantages of Convolutional Neural Networks (CNN) for MRI acceleration have been widely reported, but one remaining problem is that the significantly complex network makes itself less explainable than conventional model-based methods. In this work, a novel deep learning assisted MRI acceleration method is introduced to address the uncertainty of CNN by integrating its output as another constraint into the framework of Compressed Sensing (CS).

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