MIDL 2020 MRI Reconstruction Challenge

Researchers Jonas Teuwen and Nikita Moriakov of the Diagnostic Image Analysis Group of the Radboud University Medical Center together with colleagues from the Netherlands Cancer Institute and the Amsterdam Medical Center won an international competition where MRI-scans can be accelerated using deep learning algorithms. Their deep learning algorithm won the competition resulting in images of high quality within 2 minutes of scanning.

The competition which was part of MIDL 2020 was organized by universities in Canada and Brazil who have provided more than 100 brain MRI scans to train the algorithm. The team won both tracks of the challenge, where in the first track the goal was to reconstruct data similar to the training data with 5 and 10 times acceleration, and the second track where the algorithms had to reconstruct out-of-distribution data of a different scanner with different coil configurations. The reconstruction framework is published under an open source license on GitHub, including the winning algorithm.

The methods developed in the challenge have tight connections to our current research lines in MRI-guided radiotherapy where the patient anatomy can be visualized during radiation treatment using the builtin MRI scanner. Fast reconstruction algorithms such as the ones in the challenge open opportunities to track second-by-second patient motion.

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