Paper Info
Title
A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages
Abstract
Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However. extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.
Year
DOI
Venue
2006
10.1117/12.652919
Proceedings of SPIE
Keywords
Field
DocType
parametric deformable models,surface extraction,parameterization,subdivision surfaces,3D statistical shape models
Computer vision,Parametrization,Pattern recognition,Medical imaging,Interpolation,Subdivision,Subdivision surface,Parametric statistics,Statistical shape modeling,Artificial intelligence,Geography
Conference
Volume
ISSN
Citations 
6141
0277-786X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jurgen Fripp135444.54
Stuart Crozier213014.02
Simon K. Warfield32825229.11
Sébastien Ourselin457657.16