BCSS

The BCSS (Breast Cancer Semantic Segmentation) consists of extracts from 151 WSI images from TCGA, containing over 20,000 segmentation annotations covering 21 different tissue types.

Raw data

Key stats


Modality	Vision (WSI extracts)
Task	Segmentation - 22 classes (tissue types)
Data size	total: ~5GB
Image dimension	~1000-3000 x ~1000-3000 x 3
Magnification (μm/px)	40x (0.25)
Files format	`.png` images / `.mat` segmentation masks
Number of images	151
Splits in use	Train, Val and Test

Organization

The data is organized as follows:

bcss
├── rgbs_colorNormalized       # wsi images
│   ├── TCGA-*.png
├── masks                      # segmentation masks
│   ├── TCGA-*.png             # same filenames as images

Download and preprocessing

The BCSS dataset class doesn't download the data during runtime and must be downloaded manually from links provided here.

Although the original images have a resolution of 0.25 microns per pixel (mpp), we extract patches at 0.5 mpp for evaluation. This is because using the original resolution with common foundation model patch sizes (e.g. 224x224 pixels) would result in regions that are too small, leading to less expressive segmentation masks and unnecessarily complicating the task.

Splits

As a test set, we use the images from the medical institues OL, LL, E2, EW, GM, and S3, as proposed by the authors. For the validation split, we use images from the institutes BH, C8, A8, A1 and E9, which results in the following dataset sizes:

Splits	Train	Validation	Test
#Samples	76 (50.3%)	30 (19.9%)	45 (29.8%)

Relevant links

License

The BCSS dataset is held under the CC0 1.0 UNIVERSAL license.