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• W2903642908 abstract "Objective: We propose a novel method to map patient-specific blood velocity profiles (obtained from imaging data such as two-dimensional flow MRI or three-dimensional color Doppler ultrasound) to geometric vascular models suitable to perform computational fluid dynamics simulations of haemodynamics. We describe the implementation and utilization of the method within an open-source computational hemodynamics simulation software (CRIMSON). Methods: The proposed method establishes pointwise correspondences between the contour of a fixed geometric model and time-varying contours containing the velocity image data, from which a continuous, smooth, and cyclic deformation field is calculated. Our methodology is validated using synthetic data and demonstrated using two different in vivo aortic velocity datasets: a healthy subject with a normal tricuspid valve and a patient with a bicuspid aortic valve. Results: We compare our method with the state-of-the-art Schwarz-Christoffel method in terms of preservation of velocities and execution time. Our method is as accurate as the Schwarz-Christoffel method, while being over eight times faster. Conclusions: Our mapping method can accurately preserve either the flow rate or the velocity field through the surface and can cope with inconsistencies in motion and contour shape. Significance: The proposed method and its integration into the CRIMSON software enable a streamlined approach toward incorporating more patient-specific data in blood flow simulations." @default.
• W2903642908 created "2018-12-22" @default.
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• W2903642908 date "2019-07-01" @default.
• W2903642908 modified "2023-10-17" @default.
• W2903642908 title "Optimal B-Spline Mapping of Flow Imaging Data for Imposing Patient-Specific Velocity Profiles in Computational Hemodynamics" @default.
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• W2903642908 doi "https://doi.org/10.1109/tbme.2018.2880606" @default.
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• W2903642908 hasPublicationYear "2019" @default.
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