Segmentation of Brain MRI with Tumor by Image Overlapping using Cellular Automata

Abstract

In order to improve the health care reach, we need efficient and fast computer aided simulation processes or algorithms. When some change is found in pathological reports and biomedical quantities, the person is susceptible to diseases. If the diseases are detected earlier then there can be increase in the rate of mortality. Tumor is one such disease which has been seen to be one of the most fatal for human beings. Detecting and removing tumor is big challenge for medical practitioners. Medical image processing can be used through cellular automata has proven to be one of the fast and reliable method for detection of tumor cells. To study the capabilities of medical science CA’s are being used extensively, as they are useful in studying the self-reproducing biological systems. Purpose: This paper presents an algorithm for segmentation of MRI image through cellular automata, using Conway’s Game of Life. A new approach is being used in this paper, first the image is converted into gray level image. Then edge detection is done for this image using Game of Life. This edge detected image is overlapped with the gray scale image to get the resulted segmented image as an output. Materials and Methods: In order to run the proposed algorithm MATLAB2019b is used and the images are obtained. Results: Algorithm was used on different MRI’s and the results were taken.