UNSUPERVISED LEARNING TECHNIQUES USING SOFT COMPUTING APPROACH WITH MRI BRAIN IMAGE-A PROCESS
Journal Title: World Journal of Engineering Research and Technology - Year 2018, Vol 4, Issue 1
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.
Authors and Affiliations
Sudha Tiwari
Keywords
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UNSUPERVISED LEARNING TECHNIQUES USING SOFT COMPUTING APPROACH WITH MRI BRAIN IMAGE-A PROCESS
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 diffe...