Introduction and Acknowledgements
Acknowledgements: This work is part of Slicer Shape Analysis Toolbox (SlicerSALT), funded by NIH NIBIB R01EB021391 (Shape Analysis Toolbox for Medical Image Computing Projects), as well as the Slicer community.
Author: Zhiyuan Liu
Contributors: Pablo Hernandez-Cerdan, Jean-Christophe Fillion-Robin, Beatriz Paniagua, Jared Vicory, Junpyo Hong, Stephen M. Pizer
Contact: Zhiyuan Liu, zhiy at cs dot unc dot edu
This extension is an open source tool to initialize, refine and visualize skeletal representation (abbreviated as s-rep) of 3D objects in biomedical images. The main features of this extension include:
- Initialize an s-rep by mean curvature flow of an object boundary
- Refine an s-rep to fit an object boundary
- Visualize the s-rep
S-reps have a number of advantages in shape analysis of human organs. Some previous research has shown the superiority of using s-reps to perform hypothesis testing, classification and shape distribution analysis.
- Skeletal Representation Initializer
- Skeletal Representation Refiner
- Skeletal Representation Visualizer
Sample data can be found here.
- Stephen M. Pizer, Junpyo Hong, Jared Vicory, J. S. Marron, and others, "Object Shape Representation via Skeletal Models (s-reps) and Statistical Analysis" in Riemannian Geometric Statistics in Medical Image Analysis, no. (Xavier Pennec, Stefan Sommer, and Tom Fletcher, eds.), 2019.
- Source code can be found https://github.com/KitwareMedical/SlicerSkeletalRepresentation