1 March 2011 3D shape decomposition and comparison for gallbladder modeling
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Abstract
This paper presents an approach to gallbladder shape comparison by using 3D shape modeling and decomposition. The gallbladder models can be used for shape anomaly analysis and model comparison and selection in image guided robotic surgical training, especially for laparoscopic cholecystectomy simulation. The 3D shape of a gallbladder is first represented as a surface model, reconstructed from the contours segmented in CT data by a scheme of propagation based voxel learning and classification. To better extract the shape feature, the surface mesh is further down-sampled by a decimation filter and smoothed by a Taubin algorithm, followed by applying an advancing front algorithm to further enhance the regularity of the mesh. Multi-scale curvatures are then computed on the regularized mesh for the robust saliency landmark localization on the surface. The shape decomposition is proposed based on the saliency landmarks and the concavity, measured by the distance from the surface point to the convex hull. With a given tolerance the 3D shape can be decomposed and represented as 3D ellipsoids, which reveal the shape topology and anomaly of a gallbladder. The features based on the decomposed shape model are proposed for gallbladder shape comparison, which can be used for new model selection. We have collected 19 sets of abdominal CT scan data with gallbladders, some shown in normal shape and some in abnormal shapes. The experiments have shown that the decomposed shapes reveal important topology features.
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Weimin Huang, Weimin Huang, Jiayin Zhou, Jiayin Zhou, Jiang Liu, Jiang Liu, Jing Zhang, Jing Zhang, Tao Yang, Tao Yang, Yi Su, Yi Su, Gim Han Law, Gim Han Law, Chee Kong Chui, Chee Kong Chui, Stephen Chang, Stephen Chang, "3D shape decomposition and comparison for gallbladder modeling", Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79642K (1 March 2011); doi: 10.1117/12.878016; https://doi.org/10.1117/12.878016
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