BreakHis
The Breast Cancer Histopathological Image Classification (BreakHis) is composed of 9,109 microscopic images of breast tumor tissue collected from 82 patients using different magnifying factors (40X, 100X, 200X, and 400X). For this benchmark we only use the 40X samples which results in a subset of 1,995 images. This database has been built in collaboration with the P&D Laboratory, Pathological Anatomy and Cytopathology, Parana, Brazil.
The dataset is divided into two main groups: benign tumors and malignant tumors. The original dataset contains four histological distinct types of benign breast tumors: adenosis (A), fibroadenoma (F), phyllodes tumor (PT), and tubular adenona (TA); and four malignant tumors (breast cancer): carcinoma (DC), lobular carcinoma (LC), mucinous carcinoma (MC) and papillary carcinoma (PC).
Given that patient counts for some classes are very low (e.g. 3 for PT), we only use classes with at least 7 patients for this benchmark: TA, MC, F & DC.
Raw data
Key stats
| Modality | Vision (WSI patches) |
| Task | Multiclass classification (4 classes) |
| Cancer type | Breast |
| Data size | 4 GB |
| Image dimension | 700 x 460 |
| Magnification (μm/px) | 40x (0.25) |
| Files format | png |
| Number of images | 1471 |
Splits
The data source provides train/validation splits. There is no overlap of patients between the splits, and a stratified distribution of the classes is approximated (extact stratification is not possible due to the patient separation constraint).
| Splits | Train | Validation |
|---|---|---|
| #Samples | 1132 (76.95%) | 339 (23.04%) |
Organization
The BreakHis data is organized as follows:
BreaKHis_v1
├── histology_slides
│ ├── breast
| │ ├── benign
| │ | ├── SOB
| │ | | ├── adenosis
| │ | | ├── fibroadenoma
| │ | | └── ...
Download and preprocessing
The BreakHis dataset class supports downloading the data during runtime through setting the environment variable DOWNLOAD_DATA=true.