Biomedical Image Processing / Medical Image Processing
Pedram Masaeli; Hamid Behnam; Zahra Alizadeh Sani; Ahmad Shalbaf
Volume 7, Issue 3 , June 2013, , Pages 237-254
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 general and regional movement of left ventricle of heart (Normal, Hypokinetic and Akinetic). The ...
Read More
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 general and regional movement of 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 view of the heart walls, valves and beginning of main arteries can be obtainbed. Due to the difficulty for the interpretation of these images, time consumption and errors in manual analysis methods, an automated analysis method is required. In this paper we calculate 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 semi-local 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 the sum of squares differences. We use gradient-descend 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 regional left ventricle then movement parameters and threshold values for the scoring of each section can be extracted. The algorithm represents significant difference between a part of the normal heart and unhealthy heart that shows potential of clinical applications of the proposed method.
