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Reseach Article

An Efficient Approach for Medical Image Classification using Association Rules

by A. Veeramuthu, S. Meenakshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 3
Year of Publication: 2014
Authors: A. Veeramuthu, S. Meenakshi
10.5120/15551-4176

A. Veeramuthu, S. Meenakshi . An Efficient Approach for Medical Image Classification using Association Rules. International Journal of Computer Applications. 90, 3 ( March 2014), 1-6. DOI=10.5120/15551-4176

@article{ 10.5120/15551-4176,
author = { A. Veeramuthu, S. Meenakshi },
title = { An Efficient Approach for Medical Image Classification using Association Rules },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 3 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume90/number3/15551-4176/ },
doi = { 10.5120/15551-4176 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:10:05.333423+05:30
%A A. Veeramuthu
%A S. Meenakshi
%T An Efficient Approach for Medical Image Classification using Association Rules
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 3
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical images are crucial in diagnosis, therapy, surgery, reference, and training. The availability of Digital radiology equipment availability has ensured that digital medical images management gets more attention now. This paper presents an automatic classification system for Computed Tomography (CT) medical images are presented in this paper. In the presented methodology, Bi-orthogonal spline wavelet was used to extract features from the brain, chest and colon CT scan images. Association Rule Mining (ARM) was used for feature reduction leading to the selection of attributes with respect to class label based on frequent sets. On feature selection the CT images are classified using Naive Bayes and k-Nearest Neighbor algorithm. The classification accuracy obtained was compared with and without feature selection using Association Rule Mining.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Classification Computed Tomography (CT) Bi-orthogonal Spline Wavelets Feature Extraction Feature Selection and Association Rule Mining (ARM).