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MHub-Slicer Integration
Key Investigators
- Leonard Nürnberg (Department of Radiology, Brigham and Women’s Hospital, Boston, MA)
- Dennis Bontempi (Department of Radiology, Brigham and Women’s Hospital, Boston, MA)
- Justin Johnson (Department of Radiology, Brigham and Women’s Hospital, Boston, MA)
- Andrey Fedorov (Department of Radiology, Brigham and Women’s Hospital, Boston, MA)
- Hugo Aerts (Department of Radiology, Brigham and Women’s Hospital, Boston, MA)
Project Description
MHub is a repository of self-contained deep-learning models trained for a wide variety of applications in the medical and medical imaging domain. MHub provides the community with reproducible and transparent AI pipelines that work out of the box as intended by the developers.
As part of our efforts, we developed a first version of a Slicer MHub extension that allows users to run different AI models directly in Slicer without the need to install potentially conflicting dependencies as part of their Slicer Python installation.
Objective
The goal of this project is to polish the extension, publish it, and further explore its potential applications and user feedback to expand the extension’s capabilities, address its limitations, and ensure its seamless integration with Slicer.
Approach and Plan
Work on identified issues/enhancements, and collect feedback from the Slicer community.
Progress and Next Steps
No response
Illustrations
Background and References
No response