A computer aided method for diagnose of the heart mitral valve diseases

Abstract

In this paper, a new computer aided diagnosis system is presented for interpretation of the Doppler signals of the heart mitral valve diseases based on the pattern recognition. This paper especially deals with the feature extraction from measured Doppler signal waveforms at the heart mitral valve using the Doppler Ultrasound. Wavelet packet transforms and power spectrum estimate using Yule-Walker AR method are used to feature extract from the Doppler signals on the time-frequency domain. Wavelet entropy method is applied to these features. The back-propagation neural network is used to classify the extracted features. The performance of the developed system has been evaluated in 105 samples that contain 39 normal and 66 abnormal subjects. The results showed that this system was effective to detect Doppler heart sounds. The correct classification was about 99% for both normal and abnormal subjects.