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Segmentation verification module for finalizing multi-label AI segmentations

Key Investigators

• Csaba Pintér (EBATINCA, Spain)
• Andrey Fedorov (BWH, USA)

Presenter location: Online

Project Description

Creating multi-label segmentation models is a challenge, because the deep learning model will try to segment all the structures that it was trained on, even if some are missing. This issue is present for vertebra segmentation, but most predominantly teeth segmentation. The Dent.AI 3D Guide dental implant planning software contains a tool for fixing the most typical errors in a user friendly way. It would be great if this tool was published as an open-source Slicer module.

Objective

1. Create an open-source Slicer extension from the Segmentation Verification widget from the Dent.AI 3D Guide custom app

Approach and Plan

1. Discuss the current Segmentation Verification widget. Is the current design satisfactory for a more generic use? Is there any other issue that needs to be handled?
2. Take the existing Segmentation Verification widget from the custom app and create a Slicer module from it
3. Create an extension containing this module

Progress and Next Steps

1. Discussion with the people interested (Andrey)
2. Create extension SegmentationVerification
3. Basic implementation is done
4. Next steps
   • Implement the show neighboring segments function
   • Handle transformed segmentations

Illustrations

Background and References

• DeepEdit paper by Andrés
• Dent.AI 3D Guide software