Abstract:While low-rank matrix prior has been exploited in dynamic MR image reconstruction and has obtained satisfying performance, low-rank tensors models have recently emerged as powerful alternative representations for three-dimensional dynamic MR datasets. In this paper, we introduce a modelbased deep learning network by learning the tensor low-rank prior of the cardiac dynamic MR images. Instead of representing the dynamic dataset as a low-rank tensor directly, we propose a learned transformation operator to explo… Show more
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