Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/57350
Title: Segmentation of neighboring organs in medical image with model competition.
Authors: Yan, P.
Shen, W.
Kassim, A.A. 
Shah, M.
Issue Date: 2005
Source: Yan, P.,Shen, W.,Kassim, A.A.,Shah, M. (2005). Segmentation of neighboring organs in medical image with model competition.. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention 8 (Pt 1) : 270-277. ScholarBank@NUS Repository.
Abstract: This paper presents a novel approach for image segmentation by introducing competition between neighboring shape models. Our method is motivated by the observation that evolving neighboring contours should avoid overlapping with each other and this should be able to aid in multiple neighboring objects segmentation. A novel energy functional is proposed, which incorporates both prior shape information and interactions between deformable models. Accordingly, we also propose an extended maximum a posteriori (MAP) shape estimation model to obtain the shape estimate of the organ. The contours evolve under the influence of image information, their own shape priors and neighboring MAP shape estimations using level set methods to recover organ shapes. Promising results and comparisons from experiments on both synthetic data and medical imagery demonstrate the potential of our approach.
Source Title: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
URI: http://scholarbank.nus.edu.sg/handle/10635/57350
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