Author(s)

S. Kara, A.Güven, M. Okandan & F. Dirgenali

Abstract

Diagnosis of heart valve stenosis through the use of artificial neural networks S. ~ a r a ' , A. ~ i i v e n ~ , M. Okandanl & F. ~ i r ~ e n a l i ] ' ~ e ~ t . of Electronics Engineering, Erciyes University, Turkey. 'civil Aviation School, Erciyes University, Turkey. Abstract One of the current practices of diagnosing valve stenosis is based on the investigation of the Doppler Ultrasound's Fast Fourier Transformation (FFT) sonogram. This method depends on the physicians' interpretation and experience and sometimes results in false diagnosis. In this study, we have facilitated Artificial Neural Networks (ANN) that will not only simplify the diagnosis but enable the physician to make a quicker judgment about the existence of stenosis, without any hesitation. The FFT sonogram of Doppler Heart Ultrasound of a healthy person very resembles to the " M letter. The ratios of the three points (First Systolic Peak, Endpoint of Diastole, Second Systolic Peak) in the M like curve are used as inputs to o

Keywords