REVIEW 1 cited by
SlicerNNInteractive: A 3D Slicer extension for nnInteractive
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
SlicerNNInteractive: A 3D Slicer extension for nnInteractive
read the original abstract
SlicerNNInteractive integrates nnInteractive, a state-of-the-art promptable deep learning-based framework for 3D image segmentation, into the widely used 3D Slicer platform. Our extension implements a client-server architecture that decouples computationally intensive model inference from the client-side interface. Therefore, SlicerNNInteractive eliminates heavy hardware constraints on the client-side and enables better operating system compatibility than existing plugins for nnInteractive. Running both the client and server-side on a single machine is also possible, offering flexibility across different deployment scenarios. The extension provides an intuitive user interface with all interaction types available in the original framework (point, bounding box, scribble, and lasso prompts), while including a comprehensive set of keyboard shortcuts for efficient workflow.
Forward citations
Cited by 1 Pith paper
-
Stacked Ensemble Learning for Abdominal Aortic Aneurysm Segmentation in CT Angiography
Stacked ensemble of nnUNetv2 variants reaches mean Dice 0.9752 and mean Separation Distance 0.4598 mm on 8 test CTA cases for AAA segmentation.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.