ROOD-MRI: Benchmarking the robustness of deep learning segmentation models to out-of-distribution and corrupted data in MRI

1 code implementation • 11 Mar 2022 • Lyndon Boone, Mahdi Biparva, Parisa Mojiri Forooshani, Joel Ramirez, Mario Masellis, Robert Bartha, Sean Symons, Stephen Strother, Sandra E. Black, Chris Heyn, Anne L. Martel, Richard H. Swartz, Maged Goubran

To address these limitations, we propose ROOD-MRI: a platform for benchmarking the Robustness of DNNs to Out-Of-Distribution (OOD) data, corruptions, and artifacts in MRI.

Benchmarking Data Augmentation +4