Titlebook: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020; 23rd International C Anne L. Martel,Purang Abolmaesumi,Leo Joskow

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Learning MRI ,-Space Subsampling Pattern Using Progressive Weight Pruningiteration of learning, we first greedily eliminate a few phases that are considered less important in the .-space according to their assigned weights, and then fine-tune the reconstruction model. In our pilot study, experiments demonstrated the robustness and superiority of our proposed method in both single- and multi-modal MRI settings.

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0302-9743 Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic..The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-bl

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Improving Amide Proton Transfer-Weighted MRI Reconstruction Using T2-Weighted Images Recurrent Feature Sharing Reconstruction network (RFS-Rec) is designed to utilize intermediate features extracted from the matched T.w image by a Convolutional Recurrent Neural Network (CRNN), so that the missing structural information can be incorporated into the undersampled APT raw image thus ef

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Joint Reconstruction and Bias Field Correction for Undersampled MR Imagingimization scheme. We use the HCP dataset as well as in-house measured images for the evaluations. We show that the proposed method improves the reconstruction quality, both visually and in terms of RMSE.

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3d-SMRnet: Achieving a New Quality of MPI System Matrix Recovery by Deep Learningrk with a 3d system matrix recovery network and show that it recovers a 3d system matrix with a subsampling factor of 64 in less than a minute and outperforms CS in terms of system matrix quality, reconstructed image quality, and processing time. The advantage of our method is demonstrated by recons

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T2 Mapping from Super-Resolution-Reconstructed Clinical Fast Spin Echo Magnetic Resonance Acquisitiosing super-resolution reconstruction from conventional T2-weighted fast spin echo sequences for 3D isotropic T2 mapping. A quantitative magnetic resonance phantom was imaged using a clinical T2-weighted fast spin echo sequence at variable echo time to allow for super-resolution reconstruction at eve