An intelligent system for diagnosis of the heart valve diseases with wavelet packet neural networks.
In this paper, an intelligent system is presented for interpretation of the Doppler signals of the heart valve diseases based on the pattern recognition. This paper especially deals with combination of the feature extraction and classification from measured Doppler signal waveforms at the heart valve using the Doppler Ultrasound. Because of this, a wavelet packet neural network model developed by us is used. The model consists of two layers: wavelet and multi-layer perceptron. The wavelet layer is used for adaptive feature extraction in the time-frequency domain and is composed of wavelet packet decomposition and wavelet packet entropy. The multi-layer perceptron used for classification is a feed-forward neural network. The performance of the developed system has been evaluated in 215 samples. The test results showed that this system was effective in detecting Doppler heart sounds. The correct classification rate was about 94% for abnormal and normal subjects.
Turkoglu
Ibrahim
I
Department of Electronics and Computer Science, Technical Education Faculty, Firat University, 23119 Elazig, Turkey. iturkoglu@firat.edu.tr
Arslan
Ahmet
A
Ilkay
Erdogan
E
D001185:Artificial Intelligence; D006349:Heart Valve Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D016571:Neural Networks, Computer; D018608:Ultrasonography, Doppler