D 2024

Brain MRI Screening Tool with Federated Learning

STOKLASA, Roman, Ioannis STATHOPOULOS, Efstratios KARAVASILIS, Efstathios EFSTATHOPOULOS, Marek DOSTÁL et. al.

Basic information

Original name

Brain MRI Screening Tool with Federated Learning

Authors

STOKLASA, Roman (703 Slovakia, guarantor, belonging to the institution), Ioannis STATHOPOULOS, Efstratios KARAVASILIS, Efstathios EFSTATHOPOULOS, Marek DOSTÁL (203 Czech Republic), Miloš KEŘKOVSKÝ (203 Czech Republic), Michal KOZUBEK (203 Czech Republic) and Luigi SERIO

Edition

Athens, Greece, 2024 IEEE International Symposium on Biomedical Imaging, p. 1-5, 5 pp. 2024

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

Organization unit

Faculty of Informatics

ISBN

979-8-3503-1333-8

Keywords in English

MRI; brain; tumor; screening; FL; federated; learning

Tags

Tags

International impact, Reviewed
Změněno: 12/9/2024 15:20, RNDr. Roman Stoklasa, Ph.D.

Abstract

V originále

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.

Links

LM2023050, research and development project
Name: Národní infrastruktura pro biologické a medicínské zobrazování
Investor: Ministry of Education, Youth and Sports of the CR, Czech BioImaging: National research infrastructure for biological and medical imaging
NU21-08-00359, research and development project
Name: Klasifikace mozkových tumorů pomocí pokročilých metod analýzy dat multimodálního MR zobrazení difuze
Investor: Ministry of Health of the CR, Classification of brain tumors using advanced techniques of multimodal diffusion MRI data, Subprogram 1 - standard