An Automated Level-Set Approach for Identification of Aortic Valve Borders in Short Axis Windows of Transesophageal Echo Sequences (TEE)

摘要

The ability to identify and quantify two (2D) and three-dimensional (3D) morphological parameters of the aortic valve (AV) apparatus from transesophageal echocardiographic (TEE) imaging constitutes a valuable tool in diagnosis, treatment and follow-up of patients with aortic valve related diseases, as well as image-based morphological assessment for surgical interventions, so there is a considerable need to develop a standardized frameworks for 2D-3D valve segmentation and shape representation. AV borders and leaflets quantification is still a challenging task, and commonly based on intensive user interaction that limits its applicability. We propose a fast and accurate model free, automated method for segmenting and extracting morphological parameters. This work integrates level-set techniques to automatically delineate and quantitatively describe aortic geometry in echocardiographic images, a challenging task that has been explored only to a limited extent. The algorithm accuracy was tested on 5 patients compared to "gold standard" manual analysis, showing strong agreement between both. The proposed technique appears promising for clinical application.