Medical image processing has emerged as a powerful way to simulate fluid flows through realistic models of complex patient-specific geometries without relying upon simplifying geometric approximations. However, image-based flow modeling processes traditionally involve several steps (e.g. image segmentation, surface mesh generation, volumetric flow mesh generation, and finally computational simulation) that must often be performed using separate pieces of software. This work presents an alternative methodology in which the entire image-based flow modeling process takes place on a Cartesian domain with the image embedded as an implicit surface, circumventing the need for complex surface meshes and body-fitted flow meshes. The complete framework is demonstrated with flow calculations performed in a computed tomography (CT) image reconstruction of an intracranial aneurysm (ICA). Flow calculations are compared against calculations performed following a standard multi-step route using the Vascular Modeling Toolkit (VMTK) [1, 2] and Fluent™ (Ansys, Inc., Lebanon, NH).

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