Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction

17 Mar 2020 Eunju Cha Gyutaek Oh Jong Chul Ye

Recently, deep learning approaches have been extensively investigated to reconstruct images from accelerated magnetic resonance image (MRI) acquisition. Although these approaches provide significant performance gain compared to compressed sensing MRI (CS-MRI), it is not clear how to choose a suitable network architecture to balance the trade-off between network complexity and performance... (read more)

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