Computational Pathology Toolbox developed by TIA Centre, University of Warwick.

Stain normalization tools for histological analysis and computational pathology

RandStainNA: Simple and efficient augmentations for histology [MICCAI 2022]

GPU-accelerated Stain Normalization and Augmentation in PyTorch

adaptive color deconvolution for paper "Zheng et al., CMPB, 2019"

Gpu accelerated vahadane stain normalization for Digital Pathology workflows.

🌟 GPU-accelerated stain normalization command line tool

Pytorch implementation of Self Attentive Adversarial Stain Normalization (SAASN).

The code for stain standardization capsule

Enhanced stain normalization for histopathology images with batch processing support. Optimized for CPU, GPU (CUDA), and MPS (Apple Silicon) devices.

Tricks based on stain variations for histology analysis

Code associated with engineering thesis "Learning-Based Staining Normalization for Improving Registration of Histology Images"

Whole Slide Image Stain Normalisation and Augmentation

GitHub repository for the augmentation described in "Clustering-based Stain Augmentation: Templates for Periodic Acid-Schiff Biopsy Images" [MICCAI / SASHIMI Workshop 2025].

stain augmentation method based on stainmix up using multiple known stain matrices.

The nnU-Net deep learning framework applied to perform 3D segmentation of cancerous tissue in medical imaging data.