Abstract:

The output data generated in whole heart simula- tions are usually single or multiple parameters at each point in the simulation space. Visualizing data sets of gigabyte size puts great stress on the hardware and can be slow and tedious. Creating animated movies to analyze the excitation propaga- tion can take hours on standard systems. We present two par- allel visualization techniques to improve rendering of large datasets from cardiac simulations.The Scalable Parallel Visualization Networking (SPVN) toolkit provides the ability to assist in optimizing the utility and functionality of the aggregate resources in visualization clusters. Run time visualization offers the opportunity to visu- alize the results of cardiac simulations on the fly on High Per- formance Computers. Parallel visualization techniques enable fast manipulation of high resolution whole heart data sets and simulation results. The SPVN system has the potential to be linked with the simulation environment similar to the run time visualization described.Future efforts will focus on creating a simulation and visu- alization environment with appropriate characteristics for clinical setting. Specifically, speed, intuitive control and the ability to render diverse signals will likely be critical to drive adoption in the clinical setting.