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Cascaded U-net with Deformable Convolution for Dynamic Magnetic Resonance Imaging

Author:Zhehong Zhang  Yuze Li  Huijun Chen  

Session Type:Digital Poster  

Session Date:Tuesday, 18 May 2021  

Topic:Machine Learning for Image Reconstruction  

Session Name:Machine Learning for Image Reconstruction  

Program Number:1947  

Room Session:Concurrent 1  

Institution:Tsinghua University  

Deep Learning Enhanced T1 Mapping and Reconstruction Framework with Spatial-temporal and Physical Constraint

A fully automated framework for intracranial vessel wall segmentation based on 3D black-blood MRI

Generation of co-registered multi-contrast MR images for carotid atherosclerosis evaluation based on a single SIMPLE sequence

Non-uniform Fast Fourier Transform via Deep Learning

Reconstruction of Undersampled Dynamic MRI Data Using Truncated Nuclear Norm Minimization and Sparsity Constraints

Type and Time of Dialysis Are Independent Indicators for Carotid Atherosclerosis in End-stage Renal Disease Patients on Dialysis