Electrical Engineering and Systems Science > Image and Video Processing
arXiv:2410.07924 (eess)
[Submitted on 10 Oct 2024]
Title:ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results
Authors:Alessia Rondinella,Francesco Guarnera,Elena Crispino,Giulia Russo,Clara Di Lorenzo,Davide Maimone,Francesco Pappalardo,Sebastiano Battiato
View a PDF of the paper titled ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results, by Alessia Rondinella and 7 other authors
View PDFHTML (experimental)Abstract:This report summarizes the outcomes of the ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation (MSLesSeg). The competition aimed to develop methods capable of automatically segmenting multiple sclerosis lesions in MRI scans. Participants were provided with a novel annotated dataset comprising a heterogeneous cohort of MS patients, featuring both baseline and follow-up MRI scans acquired at different hospitals. MSLesSeg focuses on developing algorithms that can independently segment multiple sclerosis lesions of an unexamined cohort of patients. This segmentation approach aims to overcome current benchmarks by eliminating user interaction and ensuring robust lesion detection at different timepoints, encouraging innovation and promoting methodological advances.
| Subjects: | Image and Video Processing (eess.IV); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2410.07924 [eess.IV] |
| (orarXiv:2410.07924v1 [eess.IV] for this version) | |
| https://doi.org/10.48550/arXiv.2410.07924 arXiv-issued DOI via DataCite |
Submission history
From: Alessia Rondinella [view email][v1] Thu, 10 Oct 2024 13:49:47 UTC (3,137 KB)
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View a PDF of the paper titled ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results, by Alessia Rondinella and 7 other authors
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