Intracranial Hemodynamic Parameter Determination via CT Imaging

The patent applies preliminary action by pre-determining boundary conditions from CT imaging data before performing computational fluid dynamics calculations. The method extracts vascular geometry and hemodynamic parameters from medical images in advance, prepares boundary condition models, and sets up the computational framework beforehand. This preliminary preparation reduces the complexity and time required during the actual CFD simulation while maintaining high measurement precision for hemodynamic parameters.

The patent applies copying by creating simplified boundary condition models that replicate the essential characteristics of complex physiological conditions. Instead of simulating the full complexity of actual blood flow boundary conditions, the method generates representative boundary condition models from CT imaging data that capture the key hemodynamic features. This copying approach maintains measurement precision for critical parameters while significantly reducing calculation time by avoiding unnecessary computational complexity.

The patent applies mechanics substitution by replacing complex manual or mechanical modeling processes with automated image processing and computational methods. The system uses CT angiographic and perfusion imaging data to automatically generate three-dimensional vessel models through computational algorithms rather than traditional mechanical or manual modeling techniques. This substitution maintains high measurement precision for vessel geometry while reducing the complexity of the modeling system by leveraging automated data processing and reconstruction algorithms.