In clinical practice, we often see significant delays between MRI scans and the diagnosis made by radiologists, even for severe cases. In some cases, this may be caused by the lack of additional information and clues, so even the severe cases need to wait in the queue for diagnosis. This can be avoided if there is an automatic software tool, which would supplement additional information, alerting radiologists that the particular patient may be a severe case. We are presenting an automatic brain MRI Screening Tool and we are demonstrating its capabilities for detecting tumor-like pathologies. It is the first version on the path toward a robust multi-pathology screening solution. The tool supports Federated Learning, so multiple institutions may contribute to the model without disclosing their private data.
@article{arxiv.2311.14086,
title = {Brain MRI Screening Tool with Federated Learning},
author = {Roman Stoklasa and Ioannis Stathopoulos and Efstratios Karavasilis and Efstathios Efstathopoulos and Marek Dostál and Miloš Keřkovský and Michal Kozubek and Luigi Serio},
journal= {arXiv preprint arXiv:2311.14086},
year = {2023}
}
Comments
5 pages, 2 figures. Submitted to ISBI 2024 conference