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. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius StaringEric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan Caan, Max Welling, Matthew J. Muckley, Florian Knoll

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

The 2019 fastMRI challenge was an open challenge designed to advance research in the field of machine learning for MR image reconstruction. The goal for the participants was to reconstruct undersampled MRI k-space data. The original challenge left an open question as to how well the reconstruction methods will perform in the setting where there is a systematic difference between training and test data. In this work we tested the generalization performance of the submissions with respect to various perturbations, and despite differences in model architecture and training, all of the methods perform very similarly.
Original languageEnglish
Title of host publicationMachine Learning for Medical Image Reconstruction - 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Proceedings
EditorsNandinee Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages25-34
Number of pages10
Volume12964 LNCS
ISBN (Print)9783030885519
DOIs
Publication statusPublished - 2021
Event4th International Workshop on Machine Learning for Medical Image Reconstruction, MLMIR 2021 held in Conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021 - Virtual, Online
Duration: 1 Oct 20211 Oct 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12964 LNCS

Conference

Conference4th International Workshop on Machine Learning for Medical Image Reconstruction, MLMIR 2021 held in Conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
CityVirtual, Online
Period1/10/20211/10/2021

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