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Abstract #3182

Fast Magnetic Resonance Imaging by Deep Learning the Sparsified Complex Data

Zhaoyang Jin1 and Qing-San Xiang2
1Hangzhou Dianzi University, Hangzhou, China, 2University of British Columbia, Vancouver, BC, Canada


In this study, we exploited a sparsifying deep learning method and an inverse filtering reconstruction to obtain high quality complex MR images for under-sampled MRI data. This study allows much more flexible data representations for complex MRI data training, leading to significantly higher complex reconstruction quality for practical MRI applications.

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