基于Zernike矩的心脏病检测方法

2012 International Conference on Communication, Information & Computing Technology (ICCICT) Pub Date : 2012-12-31 DOI:10.1109/ICCICT.2012.6398224

A. Das

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引用次数: 0

摘要

本文详细介绍了一种基于Zernike矩和Fuzzy-C-Means聚类的心电图像性质识别技术。该方法可以检测心电图像是属于正常心脏还是病变心脏。在第二种情况下，它也可以表明心脏疾病。该方法已在充血性心力衰竭数据库、室性心动过速数据库、心房颤动数据库和正常窦性心律数据库四个数据库上进行了测试。实验表明，该方法的成功率为98.7%。

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A Zernike Moment based methodology for heart disease detection

This paper details a Zernike Moments and Fuzzy-C-Means clustering based technique to identify the nature of an ECG image. The proposed method can detect whether the ECG image belongs to a normal heart or a diseased heart. In the second case it can indicate the disease of the heart also. The method has been tested on four databases- congestive heart failure database, ventricular tachyarrhythmia database, atrial fibrillation database and normal sinus rhythm database. The experiment shows that the proposed technique is successful in 98.7% cases.

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2012 International Conference on Communication, Information & Computing Technology (ICCICT)

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