kmmuleelab/Breast_Pathology_Image_JPG
BreastPathDB BreastPathDB is a breast cancer histopathology dataset for whole-slide image based subtype classification. It contains 770 de-identified whole-slide images, including 165 H&E slides and 605 IHC slides, with clinical subtype labels, curated metadata, and patient-level train/validation/test splits. The dataset is intended for computational pathology benchmarking, weakly supervised WSI classification, and cross-cohort method development. Browse files and metadata… See the full description on the dataset page: https://huggingface.co/datasets/kmmuleelab/Breast_Pathology_Image_JPG.
BreastPathDB
BreastPathDB is a breast cancer histopathology dataset for whole-slide image based subtype classification. It contains 770 de-identified whole-slide images, including 165 H&E slides and 605 IHC slides, with clinical subtype labels, curated metadata, and patient-level train/validation/test splits.
The dataset is intended for computational pathology benchmarking, weakly supervised WSI classification, and cross-cohort method development.
Browse files and metadata through the project website:
https://leelab.kmmu.edu.cn/PathologyRepository_Breast/
Dataset Contents
- H&E and IHC whole-slide images in SVS format.
- Breast cancer subtype labels based on clinical IHC surrogate categories.
- Structured metadata file:
BreastPathDB.csv. - Patient-level data splits to reduce leakage during model evaluation.
Citation
If you use BreastPathDB, please cite the associated BreastPathDB manuscript when available and link to the project website above. Dataset access and reuse should follow the terms provided with the release.