Скачать или смотреть Stochastic Data Assimilation for Cardiovascular Flow Reconstruction – Part 1/4

Stochastic Parameter Prediction in Cardiovascular Problems
Paper DOI: https://doi.org/10.1080/10255842.2025...

This video is part of a series showing the results of a stochastic data assimilation framework for cardiovascular flow modeling.
The method couples Computational Fluid Dynamics (CFD) with an extended Ensemble Kalman Filter (EnKF) to refine:

uncertain inlet boundary conditions (constant, time-dependent, and space–time dependent), and

the full flow state (velocity and pressure fields),
based on noisy or incomplete measurements such as 4D Flow MRI.

These animations illustrate reconstructed hemodynamic fields for both idealized and patient-specific vascular models, supporting improved analysis of cardiovascular flows and wall-shear-related diagnostics.