Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices al-lowed to develop new therapies for severe cardiac diseases like arrhyth-mias and heart failure. The skills required for such interventions are still very challenging to learn, and typically acquired over several years. Vir-tual reality simulators can reduce this burden by allowing to practice such procedures without consequences on patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, includ-ing pacing and ablation procedures. Our framework involves an efficient GPU-based electrophysiological model. Thanks to an innovative mul-tithreading approach, we reach high computational performances that allow to account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular poten-tial measurements, endocardial surface reconstruction, electrophysiology mapping, radio-frequency (RF) ablation, as well as electrical stimulation. This works is a step towards computerized medical learning curriculum

Convolution surfaces with varying radius: Formulae for skeletons made of arcs of circles and line segments

International audienceWe develop closed form formulae for the computation of the defining fields of convolutions surfaces. The formulae are obtained for power inverse kernels with skeletons made of line segments or arcs of circle. To obtain the formulae we use Creative Telescoping and describe how this technique can be used for other families of kernels and skeleton primitives. We apply the new formulae to obtain convolution surfaces around $\mathcal{G}^1$ skeletons, some of them closed curves. We showcase how the use of arcs of circles greatly improves the visualization of the surface around a general curve compared with a segment based approach

Super-helices for predicting the dynamics of natural hair

Figure 1: Left, a Super-Helix. Middle and right, dynamic simulation of natural hair of various types: wavy, curly, straight. These hairstyles were animated using N = 5 helical elements per guide strand. Simulating human hair is recognized as one of the most difficult tasks in computer animation. In this paper, we show that the Kirchhoff equations for dynamic, inextensible elastic rods can be used for accurately predicting hair motion. These equations fully account for the nonlinear behavior of hair strands with respect to bending and twisting. We introduce a novel deformable model for solving them: each strand is represented by a Super-Helix, i.e., a piecewise helical rod which is animated using the principles of Lagrangian mechanics. This results in a realistic and stable simulation, allowing large time steps. Our second contribution is an in-depth validation of the Super-Helix model, carried out through a series of experiments based on the comparison of real and simulated hair motions. We show that our model efficiently handles a wide range of hair types with a high level of realism