This paper integrates computational fluid dynamics (CFD) and radiotherapy data for accurate simulation of spatio-temporal flow and deformation in real human lung. Specifically, it utilizes a mathematical formulation that fuses the CFD predictions of lung displacement with the corresponding radiotherapy data using the theory of Tikhonov regularization. The lung is assumed to behave as a poro-elastic medium with heterogeneous Young’s modulus. The CFD scheme utilizes a flow-structure interaction model to simultaneously solve the airflow equations and structural dynamics of the lung tissue, with allowance for interaction at the interface. The simulation is performed on a 3D lung geometry reconstructed from 4D CT scan dataset of real human patients. The predicted deformation is fused with inverse estimation data by means of the fusion algorithm to obtain the optimal results.

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