An Interval Iteration Based Multilevel Thresholding Algorithm for Brain MR Image Segmentation |
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| Authors: | Yuncong Feng Wanru Liu Xiaoli Zhang Zhicheng Liu Yunfei Liu Guishen Wang |
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| Institution: | 1.College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China; (Y.F.); (W.L.); (Z.L.); (Y.L.); (G.W.);2.Artificial Intelligence Research Institute, Changchun University of Technology, Changchun 130012, China;3.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;4.College of Computer Science and Technology, Jilin University, Changchun 130012, China |
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| Abstract: | In this paper, we propose an interval iteration multilevel thresholding method (IIMT). This approach is based on the Otsu method but iteratively searches for sub-regions of the image to achieve segmentation, rather than processing the full image as a whole region. Then, a novel multilevel thresholding framework based on IIMT for brain MR image segmentation is proposed. In this framework, the original image is first decomposed using a hybrid L1 − L0 layer decomposition method to obtain the base layer. Second, we use IIMT to segment both the original image and its base layer. Finally, the two segmentation results are integrated by a fusion scheme to obtain a more refined and accurate segmentation result. Experimental results showed that our proposed algorithm is effective, and outperforms the standard Otsu-based and other optimization-based segmentation methods. |
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| Keywords: | image segmentation multilevel thresholding interval iteration layer decomposition segmentation fusion |
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