Improved Edge Detection Algorithm for Brain Tumor Segmentation | Zendy

Asra Aslam | Zendy; Ekram Khan | Zendy; M. M. Sufyan Beg | Zendy

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Improved Edge Detection Algorithm for Brain Tumor Segmentation

Author(s) -

Asra Aslam,

Ekram Khan,

M. M. Sufyan Beg

Publication year - 2015

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2015.08.057

Subject(s) - sobel operator , computer science , thresholding , artificial intelligence , segmentation , edge detection , image segmentation , computer vision , enhanced data rates for gsm evolution , pattern recognition (psychology) , image (mathematics) , algorithm , image processing

Image 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

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