Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge

Knoll F, Murrell T, Sriram A, Yakubova N, Zbontar J, Rabbat M, Defazio A, Muckley MJ, Sodickson DK, Zitnick CL, Recht MP (2020)

Publication Type: Journal article

Publication year: 2020

Journal

Magnetic Resonance in Medicine Wiley

Book Volume: 84

Pages Range: 3054-3070

Journal Issue: 6

DOI: 10.1002/mrm.28338

Abstract

Purpose: To advance research in the field of machine learning for MR image reconstruction with an open challenge. Methods: We provided participants with a dataset of raw k-space data from 1,594 consecutive clinical exams of the knee. The goal of the challenge was to reconstruct images from these data. In order to strike a balance between realistic data and a shallow learning curve for those not already familiar with MR image reconstruction, we ran multiple tracks for multi-coil and single-coil data. We performed a two-stage evaluation based on quantitative image metrics followed by evaluation by a panel of radiologists. The challenge ran from June to December of 2019. Results: We received a total of 33 challenge submissions. All participants chose to submit results from supervised machine learning approaches. Conclusions: The challenge led to new developments in machine learning for image reconstruction, provided insight into the current state of the art in the field, and highlighted remaining hurdles for clinical adoption.

Authors with CRIS profile

Florian Knoll

Involved external institutions

New York University (NYU) US United States (USA) (US) Facebook, Inc. US United States (USA) (US)

How to cite

APA:

Knoll, F., Murrell, T., Sriram, A., Yakubova, N., Zbontar, J., Rabbat, M.,... Recht, M.P. (2020). Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. Magnetic Resonance in Medicine, 84(6), 3054-3070. https://dx.doi.org/10.1002/mrm.28338

MLA:

Knoll, Florian, et al. "Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge." Magnetic Resonance in Medicine 84.6 (2020): 3054-3070.

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