Novel lattice Boltzmann method based on integrated edge and region information for medical image segmentation
Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 2nd International Conference on Biomedical Engineering and Biotechnology, 11–13 October 2013, Wuhan, China
Affiliations: Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China
Note: [] Corresponding author: Zhuangzhi Yan. E-mail: [email protected]. This research was sponsored by the National Natural Science Foundation of China (NSFC61171146).
Abstract: The lattice Boltzmann (LB) method is a mesoscopic method based on kinetic theory and statistical mechanics. The main advantage of the LB method is parallel computation, which increases the speed of calculation. In the past decade, LB methods have gradually been introduced for image processing, e.g., image segmentation. However, a major shortcoming of existing LB methods is that they can only be applied to the processing of medical images with intensity homogeneity. In practice, however, many medical images possess intensity inhomogeneity. In this study, we developed a novel LB method to integrate edge and region information for medical image segmentation. In contrast to other segmentation methods, we added edge information as a relaxing factor and used region information as a source term. The proposed method facilitates the segmentation of medical images with intensity inhomogeneity and it still allows parallel computation. Preliminary tests of the proposed method are presented in this paper.
Keywords: active contour method, lattice Boltzmann (LB) method, level set method, partial differential equation
