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

17 March 2020

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

6 / 6 papers shown

Title
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis Yutong Chen Carola-Bibiane Schönlieb Pietro Lio' T. Leiner P. Dragotti Ge Wang Daniel Rueckert D. Firmin Guang Yang 22 87 0 23 Dec 2021
Simultaneous super-resolution and motion artifact removal in diffusion-weighted MRI using unsupervised deep learning Hyungjin Chung Jaehyun Kim J. Yoon J. Lee Jong Chul Ye DiffM MedIm 28 8 0 01 May 2021
CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN Gyutaek Oh Hyokyoung Bae Hyun-Seo Ahn Sung-Hong Park J. C. Ye MedIm 22 4 0 07 Dec 2020
Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation Gyutaek Oh J. Lee J. C. Ye 23 11 0 12 Nov 2020
Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data Hyungjin Chung Eunju Cha Leonard Sunwoo J. C. Ye MedIm 23 26 0 04 Aug 2020
Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR Yoseob Han J. Yoo J. C. Ye MedIm OOD 100 231 0 03 Mar 2017