There are 2 repositories under whole-slide-image topic.
DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
[CVPR'23] Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
:microscope: Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.
Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)
nuclei.io: Human-in-the-loop active learning framework for pathology image analysis
Python package for reading DICOM WSI file sets.
Official PyTorch implementation of our MICCAI 2022 paper: DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification.
[MedIA 2024] The implementation of AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
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
Implementation of LA_MIL, Local Attention Graph-based Transformer for WSIs, PyTorch
Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.
WSISR: Single image super-resolution for Whole slide Imaging using convolutional neural networks and self-supervised color normalization.
🚀 H2G-Net: Segmentation of breast cancer region from whole slide images
Codes available of a paper: An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Location Deep Features.
Python library for reading tiles from wsi tiff-files.
Multi-stain graph self attention multiple instance learning for histopathology Whole Slide Images - BMVC 2023
[ICCV'23] ConSlide: Asynchronous Hierarchical Interaction Transformer with Breakup-Reorganize Rehearsal for Continual Whole Slide Image Analysis
A simple web application for for viewing and navigating pathology whole-slide-images in your browser.
Implementation of "Dynamic Policy-Driven Adaptive Multi-Instance Learning for Whole Slide Image Classification", (CVPR 2024 Highlight).
Feature extraction from GEOJson nuclei and tissue segmentation maps
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.
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 .
Code to reproduce results of the Gigapixel Histopathological Image Analysis Using Attention-Based Neural Networks paper.
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.
[AAAI'23] MulGT: Multi-task Graph-Transformer with Task-aware Knowledge Injection and Domain Knowledge-driven Pooling for Whole Slide Image Analysis
Official Pytorch Code of Our Paper: Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need
The implementation of our MLMI19 oral paper "WSI-Net: Branch-based and Hierarchy-aware Network for Segmentation and Classification of Breast Histopathological Whole-slide Images."
Code for the DRA-Net
The code for LAGE-Net
The implementation of our pricai18 paper "Multiple Visual Fields Cascaded Convolutional Neural Network for Breast Cancer Detection."