Paper
27 March 2009 Shape-based diagnosis of the aortic valve
Razvan Ioan Ionasec, Alexey Tsymbal, Dime Vitanovski, Bogdan Georgescu, S. Kevin Zhou, Nassir Navab, Dorin Comaniciu
Author Affiliations +
Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 725908 (2009) https://doi.org/10.1117/12.812488
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Disorders of the aortic valve represent a common cardiovascular disease and an important public-health problem worldwide. Pathological valves are currently determined from 2D images through elaborate qualitative evalu- ations and complex measurements, potentially inaccurate and tedious to acquire. This paper presents a novel diagnostic method, which identies diseased valves based on 3D geometrical models constructed from volumetric data. A parametric model, which includes relevant anatomic landmarks as well as the aortic root and lea ets, represents the morphology of the aortic valve. Recently developed robust segmentation methods are applied to estimate the patient specic model parameters from end-diastolic cardiac CT volumes. A discriminative distance function, learned from equivalence constraints in the product space of shape coordinates, determines the corresponding pathology class based on the shape information encoded by the model. Experiments on a heterogeneous set of 63 patients aected by various diseases demonstrated the performance of our method with 94% correctly classied valves.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Razvan Ioan Ionasec, Alexey Tsymbal, Dime Vitanovski, Bogdan Georgescu, S. Kevin Zhou, Nassir Navab, and Dorin Comaniciu "Shape-based diagnosis of the aortic valve", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725908 (27 March 2009); https://doi.org/10.1117/12.812488
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Cited by 9 scholarly publications.
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KEYWORDS
3D modeling

Data modeling

Computer aided diagnosis and therapy

Machine learning

Pathology

Computed tomography

Visualization

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