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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/7185
Title: Computer-aided classification of the mitral regurgitation using multiresolution local binary pattern
Authors: Balodi A.
Anand, Radhey Shyam
Dewal M.L.
Rawat A.
Published in: Neural Computing and Applications
Abstract: This paper introduces a computer-aided classification (CAC) system for the severity analysis of mitral regurgitation (MR) utilizing multiresolution local binary pattern variants texture features. Initially, the Gaussian pyramid has been used as a multiresolution technique. Subsequently, seven variants of the local binary pattern (LBP) have been employed to extract the features. At last, support vector machine and random forest classifiers are used for classification. The performances of conventional LBP variants and proposed features have been evaluated on MR image database in three classes, i.e., mild, moderate, and severe, in three different views. The Gaussian pyramid-based center-symmetric local binary pattern performed well in all three views. The achieved classification accuracies are 95.66 ± 0.98% in the apical 2 chamber, 94.47 ± 1.91% in the apical 4 chamber and 94.21 ± 1.31% in parasternal long axis views using SVM classifier with the tenfold cross-validation. The outcomes of paper confirm that the performance of the conventional LBP features is enhanced significantly and the proposed CAC system is useful in assisting cardiologists in the severity analysis of MR. © 2019, Springer-Verlag London Ltd., part of Springer Nature.
Citation: Neural Computing and Applications (2020), 32(7): 2205-2215
URI: https://doi.org/10.1007/s00521-018-3935-x
http://repository.iitr.ac.in/handle/123456789/7185
Issue Date: 2020
Publisher: Springer
Keywords: Computer-aided classification system
Gaussian pyramid
Local binary patterns
Mitral regurgitation
Texture analysis
ISSN: 9410643
Author Scopus IDs: 57170651100
56363331000
6603331083
57189368127
Author Affiliations: Balodi, A., Department of Electrical Engineering, Indian Institute of Technology, Roorkee, India
Anand, R.S., Department of Electrical Engineering, Indian Institute of Technology, Roorkee, India
Dewal, M.L., Department of Electrical Engineering, Graphic Era University, Dehradun, India
Rawat, A., Department of Cardiology, Swami Rama Himalayan University, Dehradun, India
Funding Details: The author would like to thank the Ministry of Human Resource Development, Government of India, for providing financial assistance. Authors also thank the Indian Institute of Technology, Roorkee, India, for providing research facilities. The authors would also like to extend the deepest and sincere appreciations to the Department of Cardiology, Swami Rama Himalayan University, Dehradun, India, for providing the dataset of ultrasound images and their constant support for carrying out this research.
Corresponding Author: Balodi, A.; Department of Electrical Engineering, Indian Institute of TechnologyIndia; email: drbalodi@gmail.com
Appears in Collections:Journal Publications [EE]

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