相关论文: Resolving Variable Respiratory Motion From Unsorte…

Crash simulations play an essential role in improving vehicle safety, design optimization, and injury risk estimation. Unfortunately, numerical solutions of such problems using state-of-the-art high-fidelity models require significant…

Respiratory motion can cause strong blurring artifacts in the reconstructed image during MR acquisition. These artifacts become more prominent when use in the presence of undersampled data. Recently, compressed sensing (CS) is developed as…

Computational Fluid Dynamics (CFD) is used to assist in designing artificial valves and planning procedures, focusing on local flow features. However, assessing the impact on overall cardiovascular function or predicting longer-term…

This article presents an original methodology for the prediction of steady turbulent aerodynamic fields. Due to the important computational cost of high-fidelity aerodynamic simulations, a surrogate model is employed to cope with the…

The increased penetration of wind power introduces more operational changes of critical corridors and the traditional time-consuming transient stability constrained total transfer capability (TTC) operational planning is unable to meet the…

Conventional computed tomography (CT) lacks the ability to capture dynamic, weight-bearing joint motion. Functional evaluation, particularly after surgical intervention, requires four-dimensional (4D) imaging, but current methods are…

Objective: Deep learning-based deformable image registration has achieved strong accuracy, but remains sensitive to variations in input image characteristics such as artifacts, field-of-view mismatch, or modality difference. We aim to…

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive…

Modeling groundwater flow in three-dimensional fractured crystalline media requires accounting for strong spatial heterogeneity induced by fractures. Fine-scale discrete fracture-matrix (DFM) simulations can capture this complexity but are…

Driven by increased complexity of dynamical systems, the solution of system of differential equations through numerical simulation in optimization problems has become computationally expensive. This paper provides a smart data driven…

Motion during acquisition of a set of projections can lead to significant motion artifacts in computed tomography reconstructions despite fast acquisition of individual views. In cases such as cardiac imaging, motion may be unavoidable and…

Image quality of PET reconstructions is degraded by subject motion occurring during the acquisition. MR-based motion correction approaches have been studied for PET/MR scanners and have been successful at capturing regular motion patterns,…

The steep dose gradients obtained with pencil beam scanning allow for precise tumor targeting at the cost of high sensitivity to uncertainties. Robust optimization is commonly applied to mitigate uncertainties in density and patient setup,…

Intraoperative Cone Beam Computed Tomography (CBCT) provides a reliable 3D anatomical context essential for interventional planning. However, its static nature fails to provide continuous monitoring of soft-tissue deformations induced by…

Continuous protocols for cardiac magnetic resonance imaging enable sampling of the cardiac anatomy simultaneously resolved into cardiac phases. To avoid respiration artifacts, associated motion during the scan has to be compensated for…

This paper presents a physics and data co-driven surrogate modeling method for efficient rare event simulation of civil and mechanical systems with high-dimensional input uncertainties. The method fuses interpretable low-fidelity physical…

We introduce a method to construct a stochastic surrogate model from the results of dimensionality reduction in forward uncertainty quantification. The hypothesis is that the high-dimensional input augmented by the output of a computational…

The world faces a shortage of radiologists, leading to longer treatment times and increased stress, negatively impacting patient safety and workforce morale. Integrating artificial intelligence to interpret radiographic images and generate…

Objectives: The main objective of this review article is to evaluate the usability of Computational Fluid Dynamics (CFD) as a supporting clinical tool for respiratory system. Data Source: The English articles referred for this review paper…

Image-based computational fluid dynamics (CFD) modeling enables derivation of hemodynamic information, which has become a paradigm in cardiovascular research and healthcare. Nonetheless, the predictive accuracy largely depends on precisely…