Brain MRI Screening Tool with Federated Learning

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Authors

STOKLASA Roman STATHOPOULOS Ioannis KARAVASILIS Efstratios EFSTATHOPOULOS Efstathios DOSTÁL Marek KEŘKOVSKÝ Miloš KOZUBEK Michal SERIO Luigi

Year of publication 2024
Type Article in Proceedings
Conference 2024 IEEE International Symposium on Biomedical Imaging
MU Faculty or unit

Faculty of Informatics

Citation
Doi http://dx.doi.org/10.1109/ISBI56570.2024.10635396
Keywords MRI; brain; tumor; screening; FL; federated; learning
Description 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. The tool detected 98% of brain tumors in our testing dataset (102 patients) with a precision of 91 %, achieving a segmentation Dice score more than 0.88.
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