Paper
1 March 2011 A novel hybrid model for deformable image registration in abdominal procedures
Xishi Huang, Paul S. Babyn, Thomas Looi, Peter C. W. Kim
Author Affiliations +
Abstract
We propose a novel neuro-fuzzy hybrid transformation model for deformable image registration in intra-operative image guided procedures involving large soft tissue deformation. The hybrid model consists of two parts: a physics-based model and a mathematical approximation model. The physics-based model is based on elastic solid mechanics to model major deformation patterns of the central part of organs, and the mathematical approximation model depicts the deformation of the residual part along organ boundary. A neuro-fuzzy technique is employed to seamlessly integrate the two parts into a unified hybrid model. Its unique feature is to incorporate domain knowledge of soft tissue deformation patterns and significantly reduce the number of transformation parameters. We demonstrate the effectiveness of our hybrid model to register liver magnetic resonance (MR) images in human subject study. This technique has the potential to significantly improve intra-operative image guidance in abdominal and thoracic procedures.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xishi Huang, Paul S. Babyn, Thomas Looi, and Peter C. W. Kim "A novel hybrid model for deformable image registration in abdominal procedures", Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79640K (1 March 2011); https://doi.org/10.1117/12.878068
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Image registration

Liver

Mathematical modeling

Magnetic resonance imaging

Tissues

Motion models

Image segmentation

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