Abstract. The aim of this project is to validate the Vivabrain pipeline with a physical phantom from real MRI acquisition to MRI simulations through image segmentation and computational fluid dynamics (CFD) simulations. For that purpose, we set up three comparison benchmarks. The first benchmark compares dimensions of the reconstructed geometry from real MRI acquisition to the physical phantom dimensions. The second aims to validate the CFD simulations by comparing the outputs of two simulations, one carried out using Feel++ and the other using FreeFem++. The CFD outputs are also compared to MRI flow measurement data. The goal of the last comparison benchmark is to compare the MRI simulations outputs to the numerical fluid simulations.

Abstract-Shading is an important feature for the comprehension of volume datasets, but is difficult to implement accurately. Current techniques based on pre-integrated direct volume rendering approximate the volume rendering integral by ignoring non-linear gradient variations between front and back samples, which might result in cumulated shading errors when gradient variations are important and / or when the illumination function features high frequencies. In this paper, we explore a simple approach for pre-integrated volume rendering with non-linear gradient interpolation between front and back samples. We consider that the gradient smoothly varies along a quadratic curve instead of a segment in-between consecutive samples. This not only allows us to compute more accurate shaded pre-integrated look-up tables, but also allows us to more efficiently process shading amplifying effects, based on gradient filtering. An interesting property is that the pre-integration tables we use remain two-dimensional as for usual pre-integrated classification. We conduct experiments using a full hardware approach with the Blinn-Phong illumination model as well as with a non-photorealistic illumination model.

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