The Aortic Valve (AV) is an important anatomical structure which lies on the left side of the human heart. The AV
regulates the flow of oxygenated blood from the Left Ventricle (LV) to the rest of the body through aorta. Pathologies
associated with the AV manifest themselves in structural and functional abnormalities of the valve. Clinical management
of pathologies often requires repair, reconstruction or even replacement of the valve through surgical intervention.
Assessment of these pathologies as well as determination of specific intervention procedure requires quantitative
evaluation of the valvular anatomy. 4D (3D + t) Transesophageal Echocardiography (TEE) is a widely used imaging
technique that clinicians use for quantitative assessment of cardiac structures. However, manual quantification of 3D
structures is complex, time consuming and suffers from inter-observer variability. Towards this goal, we present a semiautomated
approach for segmentation of the aortic root (AR) structure. Our approach requires user-initialized landmarks
in two reference frames to provide AR segmentation for full cardiac cycle. We use ‘coarse-to-fine’ B-spline Explicit
Active Surface (BEAS) for AR segmentation and Masked Normalized Cross Correlation (NCC) method for AR tracking.
Our method results in approximately 0.51 mm average localization error in comparison with ground truth annotation
performed by clinical experts on 10 real patient cases (139 3D volumes).