There are 2 repositories under whole-slide-image topic.
DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
Toolkit for large-scale whole-slide image processing.
A library that integrates different MIL methods into a unified framework
Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)
A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
Feather - Lightweight supervised slide foundation models (ICML 2025)
[CVPR'23] Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
nuclei.io: Human-in-the-loop active learning framework for pathology image analysis
Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
Deep Multiple Instance Learning library for Pytorch
:microscope: Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.
Python package for reading DICOM WSI file sets.
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images (Medical Image Analysis 2024)
Official PyTorch implementation of our MICCAI 2022 paper: DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification.
Re-stained whole slide image alignment
The code for Kernel attention transformer (KAT)
[MICCAI'23] HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
🚀 H2G-Net: Segmentation of breast cancer region from whole slide images
WSISR: Single image super-resolution for Whole slide Imaging using convolutional neural networks and self-supervised color normalization.
Implementation of LA_MIL, Local Attention Graph-based Transformer for WSIs, PyTorch
Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.
Official Pytorch Code of Our Paper: Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need
Implementation of "Dynamic Policy-Driven Adaptive Multi-Instance Learning for Whole Slide Image Classification", (CVPR 2024 Highlight).
Codes available of a paper: An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features.
A simple web application for for viewing and navigating pathology whole-slide-images in your browser.
AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classification
Python library for reading tiles from wsi tiff-files.
Feature extraction from GEOJson nuclei and tissue segmentation maps
[ICCV'23] ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
Multi-stain graph self attention multiple instance learning for histopathology Whole Slide Images - BMVC 2023
A cross platform version of Bio library & program. Bio is a library & program for annotating, & editing various microscopy imaging formats using Bioformats supported images. including whole slide, pyramidal & series.
Malaria Parasite Detection using Efficient Neural Ensembles. Malaria, a life threatening disease caused by the bite of the Anopheles mosquito infected with the parasite, has been a major burden towards healthcare for years leading to approximately 400,000 deaths globally every year. This study aims to build an efficient system by applying ensemble techniques based on deep learning to automate the detection of the parasite using whole slide images of thin blood smears.
Code to reproduce results of the Gigapixel Histopathological Image Analysis Using Attention-Based Neural Networks paper.
This is a viewer app that provides using to zoom and pan tools Deep Zoom Image (dzi) or Whole Slide Image (wsi) using Electron JS and OpenSeaDragon .