AI Toolkit for Healthcare Imaging
- healthcare-imaging
- deep-learning
- medical-image-computing
- medical-image-processing
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AI Toolkit for Healthcare Imaging
3D medical imaging reconstruction software
Vision-Language Pathology Foundation Model - Nature Medicine
U-Net Brain Tumor Segmentation
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.
Tools for computational pathology
Neural networks toolbox focused on medical image analysis
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".
Converts medical images to more displayable formats, e.g. NIfTI to jpg.
PyTorch Connectomics: segmentation toolbox for EM connectomics
Medical LLM agent and MRI segmentation workspace built on PharmaLLM, with LangGraph, vLLM, and BEU-Net.
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
OpenBioLink is a resource and evaluation framework for evaluating link prediction models on heterogeneous biomedical graph data.
TypeDB Bio: Biomedical Knowledge Graph
mrQA: tools for quality assurance in medical imaging datasets, including protocol compliance