28 May 2003 Physics-based shape deformations for medical image analysis
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Proceedings Volume 5014, Image Processing: Algorithms and Systems II; (2003); doi: 10.1117/12.477763
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
Powerful, flexible shape models of anatomical structures are required for robust, automatic analysis of medical images. In this paper we investigate a physics-based shape representation and deformation method in an effort to meet these requirements. Using a medial-based spring-mass mesh model, shape deformations are produced via the application of external forces or internal spring actuation. The range of deformations includes bulging, stretching, bending, and tapering at different locations, scales, and with varying amplitudes. Springs are actuated either by applying deformation operators or by activating statistical modes of variation obtained via a hierarchical regional principal component analysis. We demonstrate results on both synthetic data and on a spring-mass model of the corpus callosum, obtained from 2D mid-sagittal brain Magnetic Resonance (MR) Images.
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Ghassan Hamarneh, Tim McInerney, "Physics-based shape deformations for medical image analysis", Proc. SPIE 5014, Image Processing: Algorithms and Systems II, (28 May 2003); doi: 10.1117/12.477763; https://doi.org/10.1117/12.477763
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KEYWORDS
Lab on a chip

Principal component analysis

Shape analysis

Medical imaging

Image segmentation

Statistical analysis

Statistical modeling

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