U-Net Brain Tumor Segmentation
- tensorflow
- tensorlayer
- unet
- medical-imaging
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U-Net Brain Tumor Segmentation
Dicoogle - Open Source PACS
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.
OSS Implementation of DICOMweb standard
🧫 A curated list of resources relevant to doing Biomedical Information Extraction (including BioNLP)
Tools for computational pathology
:hospital: Medical Text Mining and Information Extraction with spaCy
Neural networks toolbox focused on medical image analysis
Electronic Health Record Analysis with Python.
Modular, Production-Ready, Open-Source EHR
An offline-first, self-hosted web app to aggregate and sync all of your medical records from your patient portals in one place.
Open Source Healthcare System for Odoo
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".
Awesome list of software that I use to do research in medical imaging.
TranslatedMedical paper writing and research assistant: 32 Agent Skills for Chinese physicians and medical graduate students, usable with Claude Code and Codex, covering topic selection, PubMed literature search, Chinese and English writing, journal selection and submission, and peer review and revision. Medical writing & research skills.
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.
Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
A C# DICOM Library
MOGONET (Multi-Omics Graph cOnvolutional NETworks) is a novel multi-omics data integrative analysis framework for classification tasks in biomedical applications.
Read and write Neuroglancer datasets programmatically.
Modular, fast NLP framework, compatible with Pytorch and spaCy, offering tailored support for French clinical notes.
One command downloads a complete offline, no-internet emergency library: local AI (CPU/GPU), document Q&A, full Wikipedia, offline maps for any country/region (default US), survival/repair/medical archives, and public-domain manuals. Asks only where to save.