Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

Bio-Formats is a Java library for reading and writing data in life sciences image file formats. It is developed by the Open Microscopy Environment. Bio-Formats is released under the GNU General Public License (GPL); commercial licenses are available from Glencoe Software.

Library for Digital Pathology Image Processing

Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024

Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks - MICCAI 2021

a browser-based DICOM viewer

A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

Conversion tool/library for converting whole slide images to DICOM

This is the official repository for our CVPR 2023 paper 'Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification'.

A pipeline to segment tissue from the background in histological images

Tool to visualize gigantic pathology images and use AI to segment cancer cells and present as an overlay

Raccoon is a NoSQL-based medical image archive for managing the DICOM images.

Simple library for preprocessing histopathological whole-slide images (WSI) into tiles (a.k.a. patches) towards deep learning

DAS-MIL: Distilling Across Scales for MILClassification of Histological WSIs

Proof of concept whole slide imaging viewer on top of Google Cloud Healthcare DICOM API.

Python scripts for automatic Whole-Slide Image preprocessing.

Official Inplementation of 《WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole Slide Images》(MICCAI 2024 Oral/ Best Paper Candidate)

The code for Kernel attention transformer (KAT)

Word Sense Induction with BERT MLM

Image filters for digital pathology: detect pen marks, background, and artifacts. Use them for preprocessing towards deep learning