Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
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Updated
Apr 29, 2024 - Python
Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering
Tools for computational pathology
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
Tools for tissue image stain normalisation and augmentation in Python 3
Deep learning library for digital pathology, with both Tensorflow and PyTorch support.
A vision-language foundation model for computational pathology - Nature Medicine
Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024
Stain normalization tools for histological analysis and computational pathology
A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images - CVPR 2023
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification
[CVPR'23] Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
🔬 Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.
A pipeline to segment tissue from the background in histological images
MICCAI2022: Multiple Instance Learning with Mixed Supervision in Gleason Grading.
Digital Pathology Whole Slide Image Analysis Toolbox
Whole Slide Digital Pathology Image Tissue Localization
WSI classification
Contains code for Semantic Segmentation of MoNuSeg 2018 challenge.
PAIP2019: Liver Cancer Segmentation
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