This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
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Unsupervised Learning for Image Registration
- image-registration
- image-alignment
- machine-learning
- deep-learning
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
- semi-supervised-learning
[IEEE TMI Best Paper Award] Official Implementation for UNet++
- medical-imaging
- segmentation
- unet
- biomedical-imaging
⚡High Performance DICOM Medical Image Parser in Go.
- dicom
- dicom-images
- golang
- golang-library
Pathology Foundation Model - Nature Medicine
- foundation
- foundation-model
- histopathology
- mahmoodlab
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.
- histopathology-images
- microscopy
- sliding-windows
- medical-image-analysis
Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
- cancer-imaging-research
- radiomics
- radiomics-features
- machine-learning
Interoperable web-based DICOM slide microscopy viewer and annotation tool
Minerva Story is an image viewer that is designed specifically to make it easy for non-expert users to interact with complex tissue images.
- minerva
- microscopy
- ome
- immunofluorescence