Paper
13 March 2006 A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages
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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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jurgen Fripp, Stuart Crozier, Simon K. Warfield, and Sébastien Ourselin "A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages", Proc. SPIE 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, 614123 (13 March 2006); https://doi.org/10.1117/12.652919
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KEYWORDS
Cartilage

3D modeling

Statistical modeling

Image segmentation

Data modeling

Image processing algorithms and systems

Bone

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