Abstract
In view of the problem of low efficiency of image segmentation with intensity inhomogeneity and the problem of the multi object image can’t be segmented, a new multi-phase image segmentation algorithm based on HLBF model is proposed. The application of magnetic resonance imaging in medicine is used to demonstrate the validity of the model. The proposed model replaces the Gauss kernel function in the original LBF model with the new kernel function to improve the time efficiency. Meanwhile, the HLBF model is further integrated into the variational level set of multi-phase image segmentation strategy to achieve the segmentation of multi-phase image with intensity inhomogeneity. Experimental results show the efficiency of the proposed method. The proposed model has advantages over the traditional segmentation method in terms of time efficiency and accuracy.
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Acknowledgement
This research is funded by the Education Department of Liaoning Province Foundation grant Number LJQ2014033 and University of Science and Technology Liaoning Foundation grant Number 2013RC08.
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Zhao, J., Wang, H., Liu, H. (2016). Multiphase Image Segmentation Based on Improved LBF Model. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2016. Lecture Notes in Computer Science(), vol 9772. Springer, Cham. https://doi.org/10.1007/978-3-319-42294-7_57
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DOI: https://doi.org/10.1007/978-3-319-42294-7_57
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