IJBTT

Discriminating Brain Tumor Segmentation Algorithms & Its Area Calculation

	International Journal of Engineering Trends and Technology (IJETT)
	© 2017 by IJETT Journal
	Volume-54 Number-2
	Year of Publication : 2017
	Authors : Bhupendra T. Jagatap, Prof. Sanjeev N. Jain
	DOI :  10.14445/22315381/IJETT-V54P220

Citation 

Bhupendra T. Jagatap, Prof. Sanjeev N. Jain "Discriminating Brain Tumor Segmentation Algorithms & Its Area Calculation", International Journal of Engineering Trends and Technology (IJETT), V54(2),141-146 December 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Image Segmentation is the process of partitioning a significant information about the image could be retaken and various analysis could be performed on that segmented image. Brain is the most important and vibrant organ of the human body. The control and coordination of all the other vibrant structure is carried out by the brain. The tumor is made by the uncontrolled multiplication of cell division. Many techniques were developed to detect and segment the brain tumor using multiple segmentation algorithms such as 1) watershed algorithm, 2) k-means clustering, 3) Fuzzy c-means clustering is carried out. This is where the division of the tumor is carried out and the centralization, the perimeter and field is the efficient algorithm that divides its features as are calculated from tumors. To detect brain tumors, scanned MRI images are given as input. The work done here helps to locate the tumor in the medical field and help greatness the patient to the treatment plan. Besides, it also reduces the time for analysis. At the end of the process the tumor is separated from the MR image, its precise position and some features also determined. It is observed that the experimental results of the thresholding and morphological process is very promising in the field of brain tumor segmentation compare with clustering methods.

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Keywords
Magnetic Resonance Image (MRI), Preprocessing and Segmentation (K-means, Fuzzy c-means, Watershed algorithm), Parameter analysis.