In this project we collected 100 + 8 whole-slide images (WSIs) for development and testing of a fully-convolutional neural network (FCNN) that can distinguish between tissue and background areas on the WSIs.
This repository contains all the code and model weights required to run the model.
- Name: Tissue-background segmentation of histopathological whole-slide images
- Model on grand-challenge: Grand-challenge algorithm
- Responsible: Peter Bandi, Geert Litjens
- Publication: Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks
- License: AGPL v3.0 for code and model weights