A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
- healthcare
- data-mining
- deep-learning
- preprocessing
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TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
U-Net Brain Tumor Segmentation
- tensorflow
- tensorlayer
- unet
- medical-imaging
Tools for computational pathology
- machine-learning
- digital-pathology
- computational-pathology
- biomedical-image-processing
Neural networks toolbox focused on medical image analysis
- python
- keras
- convolutional-neural-networks
- brain
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
Awesome list of software that I use to do research in medical imaging.
Automated 3D cell detection in very large images
- microscopy
- cell-detection
- deep-learning
- image-analysis
Deep and Machine Learning for Microscopy
- microscopy
- materials
- machine-learning
- materials-science
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
AI-based pathology predicts origins for cancers of unknown primary - Nature
- histology
- pathology
- wsi-images
- histopathology
Collection of tools and scripts useful to automate microscopy workflows in ZEN Blue using Python and Open Application Development tools and AI tools.
- python
- microscopy
- scripting
- automation
Simplifying image manipulation using GDI, Graphics32, OpenCV or Vampyre Imaging libraries
A list of awesome selected resources towards the application of machine learning in Biomedical/Healthcare Imaging, inspired by
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
- cell-annotation
- multiplexed-imaging
- mpif