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Reseach Article

A New Approach for MR Brain Image Segmentation using Intuitionistic Fuzzy Complement

by P. Dhanalakshmi, M. Kavitha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 13
Year of Publication: 2016
Authors: P. Dhanalakshmi, M. Kavitha
10.5120/ijca2016910875

P. Dhanalakshmi, M. Kavitha . A New Approach for MR Brain Image Segmentation using Intuitionistic Fuzzy Complement. International Journal of Computer Applications. 145, 13 ( Jul 2016), 27-30. DOI=10.5120/ijca2016910875

@article{ 10.5120/ijca2016910875,
author = { P. Dhanalakshmi, M. Kavitha },
title = { A New Approach for MR Brain Image Segmentation using Intuitionistic Fuzzy Complement },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 13 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 27-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number13/25341-2016910875/ },
doi = { 10.5120/ijca2016910875 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:46.906710+05:30
%A P. Dhanalakshmi
%A M. Kavitha
%T A New Approach for MR Brain Image Segmentation using Intuitionistic Fuzzy Complement
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 13
%P 27-30
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As medical images contain uncertainities there are difficulties in classification of images into homogeneous regions.In order to carry out this task,intuitive ways have been found out to interpret and describe the inherent ambiguity and vagueness in the medical images interms of intuitionistic fuzzy set theory.The comparison of Intuitionistic Fuzzy C-Means algorithm with three different type of Intuitionistic Fuzzy Generator(IFG) is presented in this paper.

References
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Index Terms

Computer Science
Information Sciences

Keywords

FCM IFCM Image segmentation Intuitionistic fuzzy complement.