mlsanityData to 14 Oct 2026

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

arXiv 2410.07924 ↗First posted 10 Oct 2024eess.IV cs.CVcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 12 of its 20 references that are in the map. First posted on arXiv 10 Oct 2024.

Builds on

12 of 20 references.

References · 12

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,525
  3. 2018Attention U-Net: Learning Where to Look for the Pancreascited by 1,435
  4. 2021UNETR: Transformers for 3D Medical Image Segmentationcited by 959
  5. 2022Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Imagescited by 830
  6. 2024U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentationcited by 419
  7. 20183D MRI brain tumor segmentation using autoencoder regularizationcited by 328
  8. 2024LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentationcited by 54
  9. 2023Progressive Random Convolutions for Single Domain Generalizationcited by 34
  10. 2021Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Reviewcited by 10
  11. 2023Boosting multiple sclerosis lesion segmentation through attention mechanismcited by 8
  12. 2023Vision Backbone Enhancement via Multi-Stage Cross-Scale Attentioncited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2025PediDemi -- A Pediatric Demyelinating Lesion Segmentation Datasetcited by 2
  2. 2025Stroke Lesion Segmentation using Multi-Stage Cross-Scale Attentioncited by 0
  3. 2025Explaining Uncertainty in Multiple Sclerosis Cortical Lesion Segmentation Beyond Prediction Errorscited by 0
  4. 2026Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Modelscited by 0