MICCAI 2013 - LNCS 8149-8151

Automated Segmentation and Geometrical Modeling of the Tricuspid Aortic Valve in 3D Echocardiographic Images

Alison M. Pouch¹, Hongzhi Wang², Manabu Takabe¹, Benjamin M. Jackson^{1, 3}, Chandra M. Sehgal², Joseph H. Gorman III^{1, 3}, Robert C. Gorman^{1, 3}, and Paul A. Yushkevich²

¹Gorman Cardiovascular Research Group, University of Pennsylvania, Philadelphia, PA, USA

²Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA

³Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA

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.

Keywords: medial axis representation, deformable modeling, multi-atlas segmentation, aortic valve, 3D echocardiography

LNCS 8149, p. 485 ff.

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