A Study on Various Image Segmentation Algorithms

Authors(2) :-S. DivyaMeena, M. Mangaleswaran

Medical images have made a great effect on medicine, diagnosis, and treatment. The most important part of image processing is image segmentation. Medical Image Segmentation is the development of programmed or semi-automatic detection of limitations within a 2D or 3D image. In medical field, image segmentation is one of the vital steps in Image identification and Object recognition. Image segmentation is a method in which large data is partitioned into small amount of data. If the input MRI image is segmented then identifying the lump attacked region will be easier for physicians. In recent days, many algorithms are proposed for the image segmentation. In this paper, an analysis is made on various segmentation algorithms for medical images. Furthermore, a comparison of existing segmentation algorithms is also discussed along with the performance measure of each.

Authors and Affiliations

S. DivyaMeena
Research scholar, School of Information Technology & Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
M. Mangaleswaran
Assistant Professor, Department of Computer Science and Engineering, Jansons Institute of Technology, Coimbatore, Tamil Nadu, India

Image segmentation, Thresholding, Clustering, Graph, Markov Random Field

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Publication Details

Published in : Volume 4 | Issue 11 | November-December 2018
Date of Publication : 2018-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 272-276
Manuscript Number : IJSRSET21841134
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

S. DivyaMeena, M. Mangaleswaran, " A Study on Various Image Segmentation Algorithms, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 11, pp.272-276, November-December-2018. Available at doi : https://doi.org/10.32628/IJSRSET21841134      Citation Detection and Elimination     |     
Journal URL : https://ijsrset.com/IJSRSET21841134

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