首个提供左右乳腺分割标注的MRI数据集，助力女性健康影像分析。
Divide and Conquer: A Large-Scale Dataset and Model for Left-Right Breast MRI Segmentation
- 构建1.3万例带左右乳腺标注的MRI数据集
- 训练出可精准分割左右乳腺的深度学习模型
- 适合乳腺影像研究与医学AI开发人员使用
我们发布了首个公开可用的乳腺MRI数据集，包含超过13,000例带有明确左右乳腺分割标签的病例。同时，我们提供了在该数据集上训练的稳健深度学习模型，用于左右乳腺分割。本工作填补了乳腺MRI分析中的关键空白，为女性健康领域先进工具的开发提供了宝贵资源。数据集和已训练模型可在 www.github.com/MIC-DKFZ/BreastDivider 公开获取。
原文摘要 · Abstract (English)
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
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