Stars
A curated list of Causality in Computer Vision
Towards a general-purpose foundation model for computational pathology - Nature Medicine
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to ex…
Preprocessing module for large histological images
Implementation of the paper "A survey on attention mechanisms for medical applications: are we moving towards better algorithms?" by Tiago Gonçalves, Isabel Rio-Torto, Luís F. Teixeira and Jaime S.…
TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
An index of algorithms for learning causality with data
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Python 3 library for the augmentation & normalization of H&E images
Official code for "Self-Supervised driven Consistency Training for Annotation Efficient Histopathology Image Analysis" Published in Medical Image Analysis (MedIA) Journal, Oct, 2021.
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
Official code for "Boundary loss for highly unbalanced segmentation", runner-up for best paper award at MIDL 2019. Extended version in MedIA, volume 67, January 2021.
Image data augmentation on-the-fly by add new class on transforms in PyTorch and torchvision.
A playbook for systematically maximizing the performance of deep learning models.
PyTorch Implementation of SimSiam from "Exploring Simple Siamese Representation Learning" by Chen et al.