20 March 2015 A liver registration method for segmented multi-phase CT images
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Abstract
In order to build high quality geometric models for liver containing vascular system, multi-phase CT series used in a computer–aided diagnosis and surgical planning system aims at liver diseases have to be accurately registered. In this paper we model the segmented liver containing vascular system as a complex shape and propose a two-step registration method. Without any tree modeling for vessel this method can carry out a simultaneous registration for both liver tissue and vascular system inside. Firstly a rigid aligning using vessel as feature is applied on the complex shape model while genetic algorithm is used as the optimization method. Secondly we achieve the elastic shape registration by combine the incremental free form deformation (IFFD) with a modified iterative closest point (ICP) algorithm. Inspired by the concept of demons method, we propose to calculate a fastest diffusion vector (FDV) for each control point on the IFFD lattice to replace the points correspondence needed in ICP iterations. Under the iterative framework of the modified ICP, the optimal solution of control points’ displacement in every IFFD level can be obtained efficiently. The method has been quantitatively evaluated on clinical multi-phase CT series.
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Shuyue Shi, Rong Yuan, Zhi Sun, Qingguo Xie, "A liver registration method for segmented multi-phase CT images", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 941331 (20 March 2015); doi: 10.1117/12.2081886; https://doi.org/10.1117/12.2081886
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