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

arXiv: https://arxiv.org/abs/2410.07924 · HTML: https://mlsanity.com/paper/2410.07924/

## 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 (most cited first, 12 of 12)

- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [UNet++: A Nested U-Net Architecture for Medical Image Segmentation](https://mlsanity.com/paper/1807.10165/) (2018)
- [Attention U-Net: Learning Where to Look for the Pancreas](https://mlsanity.com/paper/1804.03999/) (2018)
- [UNETR: Transformers for 3D Medical Image Segmentation](https://mlsanity.com/paper/2103.10504/) (2021)
- [Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images](https://mlsanity.com/paper/2201.01266/) (2022)
- [U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation](https://mlsanity.com/paper/2401.04722/) (2024)
- [3D MRI brain tumor segmentation using autoencoder regularization](https://mlsanity.com/paper/1810.11654/) (2018)
- [LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation](https://mlsanity.com/paper/2403.05246/) (2024)
- [Progressive Random Convolutions for Single Domain Generalization](https://mlsanity.com/paper/2304.00424/) (2023)
- [Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Review](https://mlsanity.com/paper/2105.04881/) (2021)
- [Boosting multiple sclerosis lesion segmentation through attention mechanism](https://mlsanity.com/paper/2304.10790/) (2023)
- [Vision Backbone Enhancement via Multi-Stage Cross-Scale Attention](https://mlsanity.com/paper/2308.05872/) (2023)

## Built on by (most cited first, 4 of 4)

- [PediDemi -- A Pediatric Demyelinating Lesion Segmentation Dataset](https://mlsanity.com/paper/2508.13239/) (2025)
- [Stroke Lesion Segmentation using Multi-Stage Cross-Scale Attention](https://mlsanity.com/paper/2501.15423/) (2025)
- [Explaining Uncertainty in Multiple Sclerosis Cortical Lesion Segmentation Beyond Prediction Errors](https://mlsanity.com/paper/2504.04814/) (2025)
- [Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Models](https://mlsanity.com/paper/2605.09666/) (2026)

## 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.