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

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)

Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification

🔬 Syntax - the arrangement of whole-slide-images and their image tiles to create well-formed computational pathology pipelines.

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.

Re-stained whole slide image alignment

[MICCAI'23] HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis

[MedIA 2024] The implementation of AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images

The code for Kernel attention transformer (KAT)

Implementation of LA_MIL, Local Attention Graph-based Transformer for WSIs, PyTorch

Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.

🚀 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.

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.