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 tissue image stain normalisation and augmentation in Python 3
Tools for computational pathology
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.
Deep learning library for digital pathology, with both Tensorflow and PyTorch support.
Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024
A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
Stain normalization tools for histological analysis and computational pathology
A vision-language foundation model for computational pathology - Nature Medicine
A pipeline to segment tissue from the background in histological images
Whole Slide Digital Pathology Image Tissue Localization
MICCAI2022: Multiple Instance Learning with Mixed Supervision in Gleason Grading.
One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification
PAIP2019: Liver Cancer Segmentation
Digital Pathology Whole Slide Image Analysis Toolbox
Learning domain-agnostic visual representation for computational pathology using medically-irrelevant style transfer augmentation
OCELOT 2023: Cell Detection from Cell-Tissue Interaction
[CVPR'23] Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)
H&E ROI-Level and WSI-Level Nuclei Segmentation with HoVer-Net
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