Personalized cardiac models have become a crucial component of the clinical workflow, especially in the context of complex cardiovascular disorders, such as valvular heart disease. In this chapter we present a comprehensive framework for the patient-specific modeling of the valvular apparatus and heart chambers from multi-modal cardiac images. An integrated model of the four heart valves and chambers is introduced, which captures a large spectrum of morphologic, dynamic and pathologic variations. The patient-specific model parameters are estimated from four-dimensional cardiac images using robust learning-based techniques. These include object localization, rigid and non-rigid motion estimation, and surface boundary estimation from dense 4D data (TEE, CT) as well as regression-based techniques for surface reconstruction from sparse 4D data (MRI). Clinical applications based on the patient-specific modeling approach are proposed for decision support in Transcatheter Aortic Valve Implantation and Percutaneous Pulmonary Valve Implantation while performance evaluation is conducted on a population of 476 patients.
CITATION STYLE
Ioan Ionasec, R., Vitanovski, D., & Comaniciu, D. (2012). Morphologica l and Functional Modeling of the Heart Valves and Chambers. In Studies in Mechanobiology, Tissue Engineering and Biomaterials (Vol. 9, pp. 157–187). Springer. https://doi.org/10.1007/8415_2011_94
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