Computer Assisted System For Classification Of Wall Thickness In Ultrasound Carotid Artery Images Using Neural Networks

Abstract

The aim is to classify the carotid artery ultrasound images. This is done by developing a system i.e. a decision making system for automated diagnosis of the  ultrasound images. The system proposed classifies the images into normal ,cardiovascular and cerebovascular  diseases. The ultrasound images are preprocessed and then for each image two contours are extracted. Inorder to classify the images the multilayer back propogation network system has been developed. The system along with the contour extraction algorithms works efficiently and results shows that this system provides an higher level of classification of the ultrasound images  with reduced time.