Early detection, segmentation and quantification of coronary artery blockage using efficient image processing technique

Abstract

This proposed method aims towards a full automation of the detection of coronary artery blockage through some image processing techniques so that the system does not have to rely on human's inspection. The goal of the research is to implement the proposed image processing techniques so the system can detect the narrowing area of the wall of coronary arteries due to the condensation of different artery blocking agents. The research suggests that the system will require a 64-slice CTA image as input. After the acquisition of the desired input image, it will go through several steps to determine the region of interest. This research proposes a two stage approach that includes the preprocessing stage and decision stage. The pre-processing stage involves common image processing strategies while the decision stage involves the extraction and calculation of two feature ratios to finally determine the intended result. In order to get more insights of the subject of these examinations, this research has proposed the use of an algorithm to create a 3-D model.