MEASURING CHOLESTEROL USING INTIMA MEDIA AND APPLYING FUZZY TECHNIQUES FOR QUALITY ENHANCEMENT

Abstract Major focus of this proposed research is to apply a fuzzy reasoning system to efficiently identify the intima media thickness of the carotid artery to measure cholesterol in any ultrasound machine. In my previous research fuzzy principles have been embedded to overcome uncertainty parameters such as pixel size variation, colour variation and orientation problems in the image processing at some level. In a more generalized way, in the current research, both heuristic patterns, the generated Intima media lines have been given importance and utilized the same as input to fuzzy reasoning modules to improve the quality of the generated intima media images in a ultrasound machine in addition to efficiently fix the uncertainty parameters such as pixel size variation, orientation, problems in the image processing. These give better results comparing to my previous research. By this research, more number of heuristic patterns have been generated and given as input to the required BPN based neural network to increase the performance of the neural network and the system picked up the correct image efficiently using the same, comparing to my previous research. Thus, using any ultrasound machine, this non-invasive sonographic examination of carotid artery with these fuzzy and neural network techniques has its potential to detect skin cholesterol and cardiovascular diseases early and efficiently. The quality enhancement here in ultrasound imaging has been taken care by fuzzy reasoning techniques.