Brain MRI Screening Tool with Federated Learning
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | 2024 IEEE International Symposium on Biomedical Imaging |
| MU Faculty or unit | |
| 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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