Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

Razvan Ioan Ionasec, B. Georgescu, E. Gassner, S. Vogt, O. Kutter, M. Scheuering, N. Navab, D. Comaniciu
Dynamic model-driven quantification and visual evaluation of the aortic valve from 4D CT
Medical Image Computing and Computer-Assisted Intervention, MICCAI, 2008, New York, USA, September 6-10 2008 (bib)

Aortic valve disease is an important cardio-vascular disorder, which affects 2.5% of the global population and often requires elaborate clinical management. Experts agree that visual and quantitative evaluation of the valve, crucial throughout the clinical workflow, is currently limited to 2D imaging which can potentially yield inaccurate measurements. In this paper, we propose a novel approach for morphological and functional quantification of the aortic valve based on a 4D model estimated from computed tomography data. A physiological model of the aortic valve, capable to express large shape variations, is generated using parametric splines together with anatomically-driven topological and geometrical constraints. Recent advances in discriminative learning and incremental searching methods allow rapid estimation of the model parameters from 4D Cardiac CT specifically for each patient. The proposed approach enables precise valve evaluation with model-based dynamic measurements and advanced visualization. Extensive experiments and initial clinical validation demonstrate the efficiency and accuracy of the proposed approach. To the best of our knowledge this is the first time such a patient specific 4D aortic valve model is proposed.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif