The XNAT ML Plugin suite was built around the now-deprecated NVIDIA Clara 2.0 style of models and training. These plugins have been deprecated and are not recommended for production use but are still available as open source resources for those who are interested.
The XNAT ML release is a stand-alone package that combines XNAT 1.8 with several platform and plugin additions to enable a baseline of Machine Learning capability. These capabilities were first demonstrated in collaboration with the NVIDIA Clara suite of medical imaging AI tools, at RSNA 2019. Since then, we have been expanding functionality, deepening integrations, and hardening features to get to the point of this release.
Release Notes
Version 1.0 of the XNAT ML Plugin suite was released alongside the release of XNAT 1.8. What has changed? See XNAT ML 1.0 Release Notes
Upgrading from XNAT ML-Beta? See here for data conversion notes: Migrating XNAT ML data from Beta to Production
Getting Started
Docker Compose Installation Instructions
Project Configuration
Container Service Configuration
PACS Configuration & Data Population
Performing Training
Workflows
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Overview of supported workflows
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Model Training: Pre-coordinated Workflow
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Model Training: Retrospective Workflow
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Inference (currently unsupported)
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Setup Tasks
Data Import and Collection
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Pushing Data from a PACS to your XNAT using the SCP Receiver
Model Training
Other Operations
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Deleting Models, Training, and Datasets