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CoNSeP

CoNSep (Colorectal Nuclear Segmentation and Phenotypes) consists of 41 1000x1000 tiles extracted from 16 WSIs of unique patients. Labels are segmentation masks which indicate if a pixel belongs to one of 7 categories of cell nuclei. In total 24,319 unique nuclei are present.

Raw data

Key stats
Modality Vision (WSI patches)
Task Segmentation - 8 classes (non-"cell nucleus" + 7 categories)
Data size total: ~800MB
Image dimension 1000 x 1000 x 3
Magnification (μm/px) 40x (0.25)
Files format .png images / .mat segmentation masks
Number of images 41
Splits in use Train and Test

Organization

The data is organized as follows:

consep
├── Train
│   ├── Images                 # raw training input images
│   │   ├── train_1.png
│   │   └── ...
│   ├── Labels                 # train segmentation labels        
│   │   ├── train_1.mat
│   │   └── ...
│   ├── Overlay                # train images with bounding boxes, not in use
├── Test
│   ├── Images                 # raw test input images
│   │   ├── test_1.png
│   │   └── ...
│   ├── Labels                 # test segmentation labels        
│   │   ├── test_1.mat
│   │   └── ...
│   ├── Overlay                # test images with bounding boxes, not in use
└── README.txt                 # data description

Download and preprocessing

Note that the CoNSeP dataset is currently not available for download. As soon as it becomes availble we will add support & instructions (monitor this issue for updates)

Splits

We work with the splits provided by the data source. Since no "validation" split is provided, we use the "test" split as validation split.

Splits Train Validation
#Samples 27 (66%) 14 (34%)

License

The CoNSeP dataset are held under the Apache 2.0 License