Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction.
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SUBMITTER: Muckley MJ
PROVIDER: S-EPMC8428775 | biostudies-literature | 2021 Sep
REPOSITORIES: biostudies-literature
Publications
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction.
Muckley Matthew J MJ Riemenschneider Bruno B Radmanesh Alireza A Kim Sunwoo S Jeong Geunu G Ko Jingyu J Jun Yohan Y Shin Hyungseob H Hwang Dosik D Mostapha Mahmoud M Arberet Simon S Nickel Dominik D Ramzi Zaccharie Z Ciuciu Philippe P Starck Jean-Luc JL Teuwen Jonas J Karkalousos Dimitrios D Zhang Chaoping C Sriram Anuroop A Huang Zhengnan Z Yakubova Nafissa N Lui Yvonne W YW Knoll Florian F
IEEE transactions on medical imaging 20210831 9
Accelerating MRI scans is one of the principal outstanding problems in the MRI research community. Towards this goal, we hosted the second fastMRI competition targeted towards reconstructing MR images with subsampled k-space data. We provided participants with data from 7,299 clinical brain scans (de-identified via a HIPAA-compliant procedure by NYU Langone Health), holding back the fully-sampled data from 894 of these scans for challenge evaluation purposes. In contrast to the 2019 challenge, w ...[more]
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