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ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results

Image and Video Processing 2024-10-11 v1 Computer Vision and Pattern Recognition
Authors: Alessia Rondinella , Francesco Guarnera , Elena Crispino , Giulia Russo , Clara Di Lorenzo , Davide Maimone , Francesco Pappalardo , Sebastiano Battiato
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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.

Keywords

medical image segmentation medical and hyperspectral imaging

Cite

@article{arxiv.2410.07924,
  title  = {ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results},
  author = {Alessia Rondinella and Francesco Guarnera and Elena Crispino and Giulia Russo and Clara Di Lorenzo and Davide Maimone and Francesco Pappalardo and Sebastiano Battiato},
  journal= {arXiv preprint arXiv:2410.07924},
  year   = {2024}
}

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R2 v1 2026-06-28T19:16:09.879Z