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Ovarian Cancer Detection and Identification Using Fuzzy C Means and Improved Sobel Edge Detection Algorithm

R. Uma, B. Sasi Prabha

Abstract


Now a day’s image processing technique are very exigent and extensively used in charitable medical area for image amplification, where the time facet is very crucial to discover the anomalous tissues, especially in various cancer such as ovarian cancer, vagina cancer, etc. Ovarian cancer is the fifth most pervasive cancer for women in India. The PET/CT scan is most persistently used device for diagnosis. In this research, well organized algorithm is proposed for ovarian cancer, edge are detected based on improved sobel edge detection algorithm and nuclei segmentation of ovarian from PET/CT scan image using Fuzzy c means clustering algorithm, the behavior patterns of the algorithm are analyzed [1].Finally, edge detected image will be binary image, this image is converted into color image using olive color map function. The olive colormap function consists of colors that are shades of green and yellow. The improved sobel edge detection algorithm takes less computational time than edge detection algorithm and it  has the greatest PSNR value than sobel edge detection algorithm.

Keywords


Image Processing, PET/CT Scan, Fuzzy C Means, Improved Sobel Edge Detection

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