Analysis of cardiac wall motion estimation methods

Cardiac disease remains a major killer in the world. Improving the management of cardiovascular disease is one of the greatest challenges facing healthcare Diagnostic techniques in cardiology require complex image analysis of single images and image sequences obtained by a variety of medical imaging modalities such as ECG gated MR, CT, and ultrasound. In particular, useful information about the cardiac function can be extracted from motion analysis of a beating heart. Accurate quantitative of heart motion and deformation are of importance for evaluating normal and abnormal cardiac physiology and mechanics. Optical flow algorithms attempt to estimate the vector field, which describes spatial movements of every image point over time, and provides important information for motion analysis. While feature-based and correlation-based optical flow methods attempt to locate features or simply track similar objects between frames, gradient -based methods calculate spatial and temporal derivatives for every position in the image and use those for estimation of the optical flow vector field. As the optical flow techniques are the most known approaches in estimating of wall motion, we decided to compare the practical algorithm based on this technique.