DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
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Updated
Apr 29, 2024 - Python
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
🔬 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
WSI classification
Re-stained whole slide image alignment
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.
The code for Kernel attention transformer (KAT)
Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.
Implementation of LA_MIL, Local Attention Graph-based Transformer for WSIs, PyTorch
[MedIA 2024] The implementation of AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
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
[MICCAI'23] HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis
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.
A simple web application for for viewing and navigating pathology whole-slide-images in your browser.
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