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| Estimation
of cardiac motion based on
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 Spanish |
| Heart motion studies are a sensitive
indicator of heart disease, in consequence, the estimation of cardiac
motion and wall deformation are important parameters for understanding
the cardiac function. In particular, the evidence of reduced transmural
strain and left ventricle (LV) torsion are both important indicators of
myocardial ischemia. The detailed deformation analysis of the heart has been performed using highly invasive approaches based either on radiopaque or sonomicrometer markers implanted in the myocardium. In these approaches, implantation of markers may by themselves alter the pattern of deformation. More recently, non-invasive techniques based on tagged Magnetic Resonance Imaging (MRI) has been used to provide accurate estimations. Several methodologies have been proposed for image analysis and for extracting parameters describing the ventricular dynamics, thus increasing the frontiers of clinical diagnoses and research on cardiovascular diseases. The complete modeling of mechanical properties of cardiac structures is a problem that remains open, however, several approaches have been proposed for the description of motion and deformations of the myocardial structure based in different cardiac imaging modalities. Clinical and research applications of cardiac image analysis are considerably extensive. However, these applications still have to overcome problems like robustness, computational complexity, 3–D interaction and clinical validation. In this research, the Analysis of left ventricle motion based in 4–D Multi Slice Computerized Tomography (MSCT) is considered. The dense displacement field is obtained based on the optimized correspondence. Parameters like LV volume, radial contraction and torsion are estimated. This project is being performed throught a cooperation between the " Laboratoire de Traitement du Signal et de L'Image (LTSI)" from University of Rennes in France and the Biomedical Engineering group (GIBULA) from Venezuela. The project is funded by the French government, the Venezuelan National Research Fund ( FONACIT) and CDCHT from Universidad de Los Andes. |