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
stnictures. However, manual quantification of 3D structures is complex, time consuming
and suffers from inter-observer variability. Towards this goal, we present a semi
automated approach for segmentation of the aortic root (AR) stnicture. 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).
