期刊
IEEE TRANSACTIONS ON CYBERNETICS
卷 43, 期 3, 页码 910-920出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMCB.2012.2218233
关键词
Fuzzy c-means (FCM); image segmentation; intensity inhomogeneity; lattice Boltzmann method (LBM); level set equation (LSE); partial differential equation (PDE)
类别
资金
- National Natural Science Foundation of China [61125204, 61172146, 41031064, 60832005, 61201293]
- Fundamental Research Funds for the Central Universities
- Ph.D. Programs Foundation of Ministry of Education of China [20090203110002]
- Ocean Public Welfare Scientific Research Project, State Oceanic Administration People's Republic of China [201005017]
In the last decades, due to the development of the parallel programming, the lattice Boltzmann method (LBM) has attracted much attention as a fast alternative approach for solving partial differential equations. In this paper, we first designed an energy functional based on the fuzzy c-means objective function which incorporates the bias field that accounts for the intensity inhomogeneity of the real-world image. Using the gradient descent method, we obtained the corresponding level set equation from which we deduce a fuzzy external force for the LBM solver based on the model by Zhao. The method is fast, robust against noise, independent to the position of the initial contour, effective in the presence of intensity inhomogeneity, highly parallelizable and can detect objects with or without edges. Experiments on medical and real-world images demonstrate the performance of the proposed method in terms of speed and efficiency.
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