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Journal of Medical Signals and Sensors، جلد ۱۱، شماره ۴، صفحات ۲۸۵-۲۹۰
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عنوان انگلیسی Brain Tumor Segmentation Using Graph Coloring Approach in Magnetic Resonance Images
چکیده انگلیسی مقاله It is important to have an accurate and reliable brain tumor segmentation for cancer diagnosis and treatment planning. There are few unsupervised approaches for brain tumor segmentation. In this paper, a new unsupervised approach based on graph coloring for brain tumor segmentation is introduced. In this study, a graph coloring approach is used for brain tumor segmentation. For this aim, each pixel of brain image assumed as a node of graph and difference between brightness of a couple of pixels considered as edge. This method was applied on T1-enhanced magnetic resonance images of low-grade and high-grade patients. Since a rigid graph was needed for graph coloring, edges must be divided into existing or nonexisting edge using a threshold. The value of this threshold has affected the accuracy of image segmentation, so the choice of the optimal threshold was important. The optimal value for this threshold was 0.42 of maximum value of difference of brightness between pixels that caused the 83.62% of correlation accuracy. The results showed that graph coloring approach can be a reliable unsupervised approach for brain tumor segmentation. This approach, as an unsupervised approach, shows better accuracy in comparison with neural networks and neuro-fuzzy networks. However, as a limitation, the accuracy of this approach is dependent on the threshold of edges.
کلیدواژه‌های انگلیسی مقاله Brain tumor, graph coloring, magnetic resonance imaging, segmentation
نویسندگان مقاله | Rouholla Bagheri
Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran


| Jalal Haghighat Monfared
Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran


| Mohammad Reza Montazeriyoun


نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/595
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Short Reports
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