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World Journal of Engineering Research and Technology

( An ISO 9001:2015 Certified International Journal )

An International Peer Reviewed Journal for Engineering Research and Technology

An Official Publication of Society for Advance Healthcare Research (Reg. No. : 01/01/01/31674/16)

ISSN 2454-695X

Impact Factor : 7.029

ICV : 79.45

WJERT Citation

  All Since 2020
 Citation  172  110
 h-index  7  5
 i10-index  1  0

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Abstract

UNSUPERVISED LEARNING TECHNIQUES USING SOFT COMPUTING APPROACH WITH MRI BRAIN IMAGE-A PROCESS

Sudha Tiwari* and S. M. Ghosh

ABSTRACT

Image Segmentation is used for analysis, identification and extracting feature of image. It has been developed for detecting and classifying the brain tumor MRI images. The objective of this paper is to compare the different techniques of segmentation that is K-means and Fuzzy C- means clustering and thresholding techniques. This paper is based on soft computing tool system for detection of brain tumor tissue with accuracy. Soft computing tool comparing all segmentation techniques simultaneously this work will perform by job scheduler, job scheduler run process and give result at a time. It reduces the time analysis for detection of brain tumor image and shows different execution time and compare for their better performance.

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