Patient-Specific Cardiac Computational Modeling Based on Left Ventricle Segmentation from Magnetic Resonance Images

This paper presents three-dimensional computational modeling of the heart's left ventricle extracted and segmented from cardiac MRI. This work basically deals with the fusion of segmented left ventricle, which is segmented using region growing method, with the generic deformable template. The multi-frame cardiac MRI image data of heart patients is taken into account. The region-based segmentation is performed in ITK-SNAP. The left ventricle is segmented in all slices in multi-frame MRI data of the whole cardiac cycle for each patient. Various parameters like myocardial muscle thickness can be calculated, which are useful for assessing cardiac function and health of a patient's heart by medical practitioners. With the left ventricle cavity and myocardium segmented, measurement of the average distance from the endocardium to the epicardium can be used to measure myocardial muscle thickness.