Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.
Publication/Presentation Date
1-1-2013
Abstract
The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.
Volume
16
Issue
Pt 1
First Page
485
Last Page
492
Published In/Presented At
Pouch, A. M., Wang, H., Takabe, M., Jackson, B. M., Sehgal, C. M., Gorman, J. H., 3rd, Gorman, R. C., & Yushkevich, P. A. (2013). Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 16(Pt 1), 485–492. https://doi.org/10.1007/978-3-642-40811-3_61
Disciplines
Medicine and Health Sciences
PubMedID
24505702
Department(s)
Department of Medicine, Cardiology Division
Document Type
Article