A system to diagnose atherosclerosis via wavelet transforms, principal component analysis and artificial neural networks


Kara S., Dirgenali F.

EXPERT SYSTEMS WITH APPLICATIONS, vol.32, no.2, pp.632-640, 2007 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 32 Issue: 2
  • Publication Date: 2007
  • Doi Number: 10.1016/j.eswa.2006.01.043
  • Title of Journal : EXPERT SYSTEMS WITH APPLICATIONS
  • Page Numbers: pp.632-640

Abstract

In this study, Doppler ultrasound signals were acquired from carotid arteries of 82 patients with atherosclerosis and 95 healthy volunteers. We have employed discrete wave transform (DWT) of Doppler signals and power spectral density graphics of these decomposed signals using Welch method. After that, we have performed Principal component analysis (PCA) for data reduction and ANN in order to distinguish between atherosclerosis and healthy subjects.