Cardiac View Classification using Speed Up Robust Features

G  N  Balaji; T  S  Subashini   and N  Chidambaram

doi:10.17485/ijst/2015/v8iS7/62245

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Cardiac View Classification using Speed Up Robust Features

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8iS7/62245

Year: 2015, Volume: 8, Issue: Supplementary 7, Pages: 1-5

Original Article

Cardiac View Classification using Speed Up Robust Features

G. N. Balaji ^{1 *}, T. S. Subashini ¹ and N. Chidambaram²

¹Department of Computer Science and Engineering, Annamalai University, Annamalai Nagar- 608002, India; [email protected] , [email protected]
² Department of Cardiology, Annamalai University, Annamalai Nagar- 608002, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Objectives: Automating cardiac view classification is the first step for automating computer aided cardiac disease diagnosis. In this paper automatic cardiac view classification system is proposed. Methods: This system attempts to classify four standard cardiac views in echocardiogram namely Parasternal Long Axis (PLAX), Parasternal Short Axis (PSAX), Apical Four Chamber (A4C), and Apical Two Chamber (A2C) views automatically using Speed Up Robust Features (SURF). Conclusion: The Speed Up Robust Features is effective in collecting more class-specific information and ro-bust in dealing with partial occlusion and viewpoint changes. To authenticate the generalizability and robustness, the proposed system is tested on a dataset of 200 echocardiogram images which achieve a classification rate of 90.7%.
Keywords: Apical Four Chamber (A4C), Apical Two Chamber (A2C), Echocardiogram, Parasternal Long Axis (PLAX), Parasternal Short Axis (PSAX), Speed Up Robust Features (SURF)