Abstract
This paper presents a novel level set method to segment medical image with intensity inhomogeneity (IIH). The multi-scale segmentation idea is incorporated and a new penalty energy term is proposed to eliminate the time-consuming re-initialization procedure. Firstly, the circular window is used to define the local region so as to approximate the image as well as IIH. Then, multi-scale statistical analysis is performed on intensities of local circular regions center in each pixel. The multi-scale energy term can be constructed by fitting multi-scale approximation of inhomogeneity-free image in a piecewise constant way. In addition, a new penalty energy term is constructed to enforce level set function to maintain a signed distance function near the zero level set. Finally, the multi-scale segmentation is performed by minimizing the total energy functional. The experiments on medical images with IIH have demonstrated the efficiency and robustness of the proposed method.
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Wang, XF., Min, H., Zou, L., Zhang, YG. (2014). Multi-scale Level Set Method for Medical Image Segmentation without Re-initialization. In: Huang, DS., Han, K., Gromiha, M. (eds) Intelligent Computing in Bioinformatics. ICIC 2014. Lecture Notes in Computer Science(), vol 8590. Springer, Cham. https://doi.org/10.1007/978-3-319-09330-7_9
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DOI: https://doi.org/10.1007/978-3-319-09330-7_9
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