Data-Driven Sonification of CFD Aneurysm Models

Abstract

A novel method is presented for inspecting and characterizing turbulent-like hemodynamic structures in intracranial cerebral aneurysms by sonification of data generated using Computational Fluid Dynamics (CFD). The intention of the current research is to intuitively communicate flow complexity by augmenting conventional flow visualizations with data-driven sound, thereby increasing the ease of interpretation of dense spatiotemporal data through multimodal presentation. The described implementation allows the user to listen to flow fluctuations thought to indicate turbulent-like blood flow patterns that are often visually difficult to discriminate in conventional flow visualizations.