ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results
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| Format: | Preprint |
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2024
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| _version_ | 1866929535682871296 |
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| author | Rondinella, Alessia Guarnera, Francesco Crispino, Elena Russo, Giulia Di Lorenzo, Clara Maimone, Davide Pappalardo, Francesco Battiato, Sebastiano |
| author_facet | Rondinella, Alessia Guarnera, Francesco Crispino, Elena Russo, Giulia Di Lorenzo, Clara Maimone, Davide Pappalardo, Francesco Battiato, Sebastiano |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_07924 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results Rondinella, Alessia Guarnera, Francesco Crispino, Elena Russo, Giulia Di Lorenzo, Clara Maimone, Davide Pappalardo, Francesco Battiato, Sebastiano Image and Video Processing Computer Vision and Pattern Recognition 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. |
| title | ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2410.07924 |