Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

Muckley MJ, Riemenschneider B, Radmanesh A, Kim S, Jeong G, Ko J, Jun Y, Shin H, Hwang D, Mostapha M, Arberet S, Nickel D, Ramzi Z, Ciuciu P, Starck JL, Teuwen J, Karkalousos D, Zhang C, Sriram A, Huang Z, Yakubova N, Lui YW, Knoll F (2021)

Publication Type: Journal article

Publication year: 2021

Journal

IEEE Transactions on Medical Imaging Institute of Electrical and Electronics Engineers (IEEE)

DOI: 10.1109/TMI.2021.3075856

Abstract

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, we focused our radiologist evaluations on pathological assessment in brain images. We also debuted a new Transfer track that required participants to submit models evaluated on MRI scanners from outside the training set. We received 19 submissions from eight different groups. Results showed one team scoring best in both SSIM scores and qualitative radiologist evaluations. We also performed analysis on alternative metrics to mitigate the effects of background noise and collected feedback from the participants to inform future challenges. Lastly, we identify common failure modes across the submissions, highlighting areas of need for future research in the MRI reconstruction community.

Authors with CRIS profile

Florian Knoll

Involved external institutions

Radboud University Nijmegen Medical Centre / Radboudumc of voluit Radboud Universitair Medisch Centrum (UMC) NL Netherlands (NL) Siemens AG, Healthcare Sector DE Germany (DE) Yonsei University KR Korea, Republic of (KR) AIRS Medical Inc. KR Korea, Republic of (KR) Commissariat à l'énergie atomique FR France (FR) École Polytechnique - Université Paris-Saclay FR France (FR) Meta, Inc. US United States (USA) (US) Amsterdam University Medical Centers (Amsterdam UMC) / Amsterdam Universitair Medische Centra NL Netherlands (NL) New York University (NYU) US United States (USA) (US)

How to cite

APA:

Muckley, M.J., Riemenschneider, B., Radmanesh, A., Kim, S., Jeong, G., Ko, J.,... Knoll, F. (2021). Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/TMI.2021.3075856

MLA:

Muckley, Matthew J., et al. "Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction." IEEE Transactions on Medical Imaging (2021).

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