3D Slicer Cast interface extension: Hub, Resource Servers and Image Display client.
Key Investigators
Martin Bellehumeur (Radical Imaging, Germany)
Andrey Fedorov (BWH, USA)
Renzo Phellan Aro (Lunenfeld-Tanenbaum Research Institute, Sinai Health, Canada)
Ahmed Rekik (École de technologie supérieure, Canada)
Jarrett Rushmore (Center for Morphometric Analysis, Massachusetts General Hospital, Boston, USA)
Sylvain Bouix (École de technologie supérieure, Canada)
Project Description
The project is about desktop integration infrastucture for healthcare applications. It introduces a new 3D Slicer extension that provides backend and front-end services to that effect.
The extension repository is here: https://github.com/mbellehumeur/SlicerCastInterface
Objective
Proof of concept global scene views to circle back to PW43 AI for personal hanging protocols project.
Demonstrate the new 3D Slicer extension with a worklist example application.
Demonstrate medical imaging resource server integration with the research of NA-MIC conference participants
Approach and Plan
Implement resource servers concept.
Implement SCENEVIEW request in the Slicer image display client
Implement cast interface in Slim
Progress and Next Steps
Three project week teams integrated their research:
Lung cancer screening with OHIF
(https://projectweek.na-mic.org/PW45_2026_Boston/Projects/ExtractingDeepLearningFeaturesFromCtImagesOfTheThoracicRegionForLungCancerApplications/)
Subcortical segmentation: with VolView.
(https://projectweek.na-mic.org/PW45_2026_Boston/Projects/Vox2SeglamProtocolGuidedSubcorticalSegmentationIn3DSlicer/)
AI search agents for IDC data with the worklist example application.
(https://projectweek.na-mic.org/PW45_2026_Boston/Projects/RedesignedRestApiAndMcpServerForImagingDataCommons/)
Illustrations
Cross-product scene views:
VolView desktop integration of AI subcortical segmentation of the brain
Imaging worklist:
IDC MCP integration in worlist
VolView using a segmentation resource server without DICOM archive:
References
Lung cancer screening:
https://projectweek.na-mic.org/PW45_2026_Boston/Projects/ExtractingDeepLearningFeaturesFromCtImagesOfTheThoracicRegionForLungCancerApplications/