Repository Index

AI Toolkit for Healthcare Imaging

• healthcare-imaging
• deep-learning
• medical-image-computing
• medical-image-processing

OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

• nci-itcr
• nci-qin
• quantitative-imaging
• imaging-informatics

Multi-platform, free open source software for visualization and image computing.

• medical-imaging
• vtk
• itk
• python

PyWavelets - Wavelet Transforms in Python

• wavelets
• wavelet-transform
• signal-processing
• image-processing

TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.

• medical-imaging
• medical-ai
• deep-learning
• machine-learning

⚡High Performance DICOM Medical Image Parser in Go.

• dicom
• dicom-images
• golang
• golang-library

3D medical imaging reconstruction software

• dicom
• dicom-viewer
• magnetic-resonance-imaging
• medical-image-processing

Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.

Spatial Single Cell Analysis in Python

• single-cell-rna-seq
• single-cell-genomics
• spatial-transcriptomics
• spatial-analysis

A pure JavaScript medical research image viewer.

Vision-Language Pathology Foundation Model - Nature Medicine

• bioimage-analysis
• bioimage-informatics
• conch
• foundation-model

Dicoogle - Open Source PACS

• dicoogle
• dicom
• pacs
• medical-imaging

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

C library for reading virtual slide images

• pathology
• whole-slide-imaging
• c

Tools for computational pathology

• machine-learning
• digital-pathology
• computational-pathology
• biomedical-image-processing

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

• artificial-intelligence
• clip
• pathology
• vision-and-language

Neural networks toolbox focused on medical image analysis

• python
• keras
• convolutional-neural-networks
• brain

Produce a sharp image of a planetary system object (moon, sun, planets) from many seeing-affected frames according to the "lucky imaging" technique.

Image restoration for fluorescence microscopy

Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".

• imaging
• ai
• cloud-computing
• medical-imaging

Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell

• histology
• wsi-images
• pan-cancer-analysis
• genomics

Automated 3D cell detection in very large images

• microscopy
• cell-detection
• deep-learning
• image-analysis

Allocators, I/O streams, math, geometry, image and audio processing for D

• utility-library
• dlang
• linear-algebra
• computational-geometry

Converts medical images to more displayable formats, e.g. NIfTI to jpg.