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24 February 2012 Dynamic shape modeling of the mitral valve from real-time 3D ultrasound images using continuous medial representation
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Abstract
Purpose: Patient-specific shape analysis of the mitral valve from real-time 3D ultrasound (rt-3DUS) has broad application to the assessment and surgical treatment of mitral valve disease. Our goal is to demonstrate that continuous medial representation (cm-rep) is an accurate valve shape representation that can be used for statistical shape modeling over the cardiac cycle from rt-3DUS images. Methods: Transesophageal rt-3DUS data acquired from 15 subjects with a range of mitral valve pathology were analyzed. User-initialized segmentation with level sets and symmetric diffeomorphic normalization delineated the mitral leaflets at each time point in the rt-3DUS data series. A deformable cm-rep was fitted to each segmented image of the mitral leaflets in the time series, producing a 4D parametric representation of valve shape in a single cardiac cycle. Model fitting accuracy was evaluated by the Dice overlap, and shape interpolation and principal component analysis (PCA) of 4D valve shape were performed. Results: Of the 289 3D images analyzed, the average Dice overlap between each fitted cm-rep and its target segmentation was 0.880±0.018 (max=0.912, min=0.819). The results of PCA represented variability in valve morphology and localized leaflet thickness across subjects. Conclusion: Deformable medial modeling accurately captures valve geometry in rt-3DUS images over the entire cardiac cycle and enables statistical shape analysis of the mitral valve.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alison M. Pouch, Paul A. Yushkevich, Benjamin M. Jackson, Joseph H. Gorman III, Robert C. Gorman, and Chandra M. Sehgal "Dynamic shape modeling of the mitral valve from real-time 3D ultrasound images using continuous medial representation", Proc. SPIE 8320, Medical Imaging 2012: Ultrasonic Imaging, Tomography, and Therapy, 832009 (24 February 2012); https://doi.org/10.1117/12.910708
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