Brain MRI Segmentation using Cellular Automata in k-Means Algorithm
Jasmeena Tariq1, A. Kumaravel2

1Jasmeena Tariq*, Computer Applications, Bharath Institute of Higher Education, Research, Chennai.
2Dr Kumaravel Professor, Dean, School of Computing, Bharath University, Chennai.

Manuscript received on October 15, 2019. | Revised Manuscript received on 27 October, 2019. | Manuscript published on November 10, 2019. | PP: 3498-3501 | Volume-9 Issue-1, November 2019. | Retrieval Number: A5095119119/2019©BEIESP | DOI: 10.35940/ijitee.A5095.119119
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Abstract: Tumors in brain have a fast growth(malignant) and should be prevented through various medical ways. However detecting these tumor cells accurately can help the medical professionals to provide accurate and hassle free diagnosis and treatment. Thus we are using Cellular Automata to provide better detection methods in an MRI(Magnetic Resonance Imaging). Cellular Automat is widely used concept with image processing. It is a system which id discreet and dynamic and comprises of simple cellular grid and rules, and works locally. Due to simplicity and usage in complex problems it is widely used concept in many new emerging data science complex problems. Conway’s Game of Life is very well known cellular automata and thus researchers are becoming more interested in CA.
Keywords: Data Mining, MRI, Data Science, Classifiers, cellular Automata, Multi-Dimensional Cellular Automata.
Scope of the Article: Data Mining