doi: 10.4304/jsw.9.9.2309-2314
Classification of Cardiac Ultrasound Image Sequences Based on Sparse Representation
- 1 Department of Computer Science and Engineering, North China Institute of Aerospace Engineering, Langfang, China
- 2 School of Computer Science and Technology, Harbin Institute of Technology, Harbin China
Abstract
To classify thrombosis and pectinate muscle incardiac ultrasound image sequences, a classification methodbased on sparse representation is proposed. This methodextracts GLCM based texture features to form the sampleset and compute the sparse solution with coefficients how atest sample be represented by the training set. After that,two kinds of constraints and classification strategy areadded to achieve the classification. Experiment resultsshows that the proposed approach can achieve aclassification accuracy of 91.92%, significantly higher thanother popular classifiers.
Keywords
- Sparse representation
- Image sequence
- Te
How to Cite
Xiaofang Hou, Penghua Zhu, and Yanxin Ma, "Classification of Cardiac Ultrasound Image Sequences Based on Sparse Representation," Journal of Software, vol. 9, no. 9, pp. 2309-2314, 2014. https://doi.org/ 10.4304/jsw.9.9.2309-2314
Copyright & License
Copyright © 2014 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).