Abstract
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.
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Veiga, C., Calvo, F., Paredes-Galán, E., Pazos, P., Peña, C., Íñiguez, A. (2014). An Automated Level-set Approach for Identification of Aortic Valve Borders in Short Axis Windows of Transesophageal Echo Sequences (TEE). In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2014. Lecture Notes in Computer Science(), vol 8815. Springer, Cham. https://doi.org/10.1007/978-3-319-11755-3_25
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DOI: https://doi.org/10.1007/978-3-319-11755-3_25
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