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Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge.

Patricia M. JohnsonGeunu JeongKerstin HammernikJo SchlemperChen QinJinming DuanDaniel RueckertJingu LeeNicola PezzottiElwin de WeerdtSahar YousefiMohamed S. ElmahdyJeroen Hendrikus Franciscus Van GemertChristophe SchülkeMariya DonevaTim NielsenSergey KastryulinBoudewijn P. F. LelieveldtMatthias J. P. van OschMarius StaringEric Z. ChenPuyang WangXiao ChenTerrence ChenVishal M. PatelShanhui SunHyungseob ShinYohan JunTaejoon EoSewon KimTaeseong KimDosik HwangPatrick PutzkyDimitrios KarkalousosJonas TeuwenNikita MiriakovBart BakkerMatthan W. A. CaanMax WellingMatthew J. MuckleyFlorian Knoll
Published in: MLMIR@MICCAI (2021)
Keyphrases
  • image reconstruction
  • image reconstruction algorithms
  • image processing
  • super resolution
  • model selection
  • training and test data
  • positron emission tomography
  • test data