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     Research Journal of Applied Sciences, Engineering and Technology


Identification of Carotid Asymptomatic Plaque Using Texture and Orientation Features for Health Care

1D. Sasikala and 2M. Madheswaran
1Department of ECE, Vivekanandha College of Engineering for Women, Tiruchengode, India
2Department of ECE, Mahendra Engineering College, Namakkal, India
Research Journal of Applied Sciences, Engineering and Technology  2014  1:56-63
http://dx.doi.org/10.19026/rjaset.8.940  |  © The Author(s) 2014
Received: February 18, 2014  |  Accepted: April ‎09, ‎2014  |  Published: July 05, 2014

Abstract

The carotid artery asymptomatic plaque identification has been done using the texture features at various orientation scales and presented in this study. The plaque region has been segmented using cubic spline interpolation method for multiresolution analysis using discrete wavelet transform. The features have been extracted using various scale and orientation of detail sub images using Gabor filters. It has been found from the analysis that the horizontal detail images have significantly greater values of the features than vertical detail images for symptomatic subjects. However, the horizontal detail images have shown low values compared to the vertical detail images for asymptomatic subjects. The algorithm is found to be simple and accurate for identifying the asymptomatic plaque clinically using less number of features.

Keywords:

Carotid artery, , discrete wavelet transform, Gabor transform , healthcare , plaque,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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