Automatic detection of coronary artery disease using registration of ultrasound images of the heart (echocardiography

Abstract

Coronary artery diseases cause more than half of all deaths in the world. Obviously, early identification is an important way to control coronary artery disease that is diagnosed by measurement and scoring the general and regional movement of the left ventricle of heart (normal, hypokinetic, and akinetic). The most common method of imaging the heart using ultrasound is called echocardiography. Using this method accurate views of the heart walls, valves, and beginning of main arteries can be obtained. Due to the difficulty of the interpretation of these images, the length of time required, and errors in manual methods, an automated analysis method is required. In line with this goal, in this paper we have calculated the displacement field in a cycle of heart motion from two-dimensional echocardiography images. To do this, a frame is usually chosen as the reference frame and then all images in a cycle are mapped to it with a mathematical equation. The main idea is to find a semilocal spatiotemporal parametric model for deformation created in a cardiac cycle with nonrigid registration using B-spline functions as an optimization problem that effectively corrects differences due to movements by minimizing the difference between current frame and a reference frame. Motion estimation accuracy is measured using sum of squares differences. We use a gradient-descent algorithm and multiresolution method to acquire the coefficients in the motion model. The accuracy of the proposed method is assessed using a synthesis sequence of cardiac cycles produced with the simulation software Field II. This algorithm can be applied for the clinical analysis of the regional left ventricle and then movement parameters and threshold values for the scoring of each section can be extracted. The algorithm represents the significant difference between a part of a normal heart and an unhealthy heart and shows the potential of the clinical applications of the proposed method.