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dc.contributor.authorAslam, Asra
dc.contributor.authorKhan, Ekram
dc.contributor.authorBeg, M.M. Sufyan
dc.identifier.citationAslam, Asra, Khan, Ekram, & Beg, M. M. Sufyan. (2015). Improved Edge Detection Algorithm for Brain Tumor Segmentation. Procedia Computer Science, 58, 430-437. doi:
dc.description.abstractImage segmentation is used to separate objects from the background, and thus it has proved to be a powerful tool in bio-medical imaging. In this paper, an Improved Edge Detection algorithm for brain-tumor segmentation is presented. It is based on Sobel edge detection. It combines the Sobel method with image dependent thresholding method, and finds different regions using closed contour algorithm. Finally tumors are extracted from the image using intensity information within the closed contours. The algorithm is implemented in C and its performance is measured objectively as well as subjectively. Simulation results show that the proposed algorithm gives superior performance over conventional segmentation methods. For comparative analysis, various parameters are used to demonstrate the superiority of proposed method over the conventional ones.en_IE
dc.relation.ispartofProcedia Computer Scienceen
dc.subjectBrain Tumor Segmentationen_IE
dc.subjectClosed Contour Algorithmen_IE
dc.subjectImproved Sobel Edge Detectionen_IE
dc.subjectSobel Edge Detection.en_IE
dc.titleImproved edge detection algorithm for brain tumor segmentationen_IE
dc.local.contactAsra Aslam, The Insight Centre For Data Analytics, Nuig, The Deri Building, The Deri Building, Ida Business Park, Lower Dangan, Galway, Ireland. - Email:

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