Published Paper Details:

The accurate and automatic segmentation of brain tumor on F- Magnetic Resonance Imaging (FMRI ) image is of great interest for assessing tumour growth and treatment responses, enhancing computer-aided surgery, planning radiation therapy, and constructing tumor growth models. The shape and boundary information of the brain tumor affected area is taken into consideration; hence, the edge detection operator is employed on different FMRI cancer tumour images. The five edge-detection methods of Sobel, Prewitt, Robert, Laplacian and Canny Operators are displayed by running MATLAB code on of FMRI cancer image. These five edge-detectors are the most commonly used techniques which are selected and tested. To smooth the image, a special approach is introduced, namely Parallel Median Method (PMM) and for removing the impulsive noise in images. The process of image smoothing is used to remove noise in the FMRI image. Initially, FMRI brain cancer image is taken, this color image is converted into gray scale image and then this gray scale image is converted into two-tone image that is binary image, for further processing of cancer affected areas in the FMRI brain cancer image.