English

Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation

Image and Video Processing 2025-07-21 v1 Computer Vision and Pattern Recognition

Abstract

We introduce the first publicly available breast MRI dataset with explicit left and right breast segmentation labels, encompassing more than 13,000 annotated cases. Alongside this dataset, we provide a robust deep-learning model trained for left-right breast segmentation. This work addresses a critical gap in breast MRI analysis and offers a valuable resource for the development of advanced tools in women's health. The dataset and trained model are publicly available at: www.github.com/MIC-DKFZ/BreastDivider

Keywords

Cite

@article{arxiv.2507.13830,
  title  = {Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation},
  author = {Maximilian Rokuss and Benjamin Hamm and Yannick Kirchhoff and Klaus Maier-Hein},
  journal= {arXiv preprint arXiv:2507.13830},
  year   = {2025}
}

Comments

Accepted at MICCAI 2025 WOMEN

R2 v1 2026-07-01T04:07:35.817Z