Vector Rendering of Biomarker Topomaps
A Comparison of Direct Vector Visualization Pipelines Against Raster Visualization Pipelines for Rendering Topomaps of EEG Biomarkers
G. Bayindir (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Arthur Avramiea – Mentor (Vrije Universiteit Amsterdam)
R. Guerra Marroquim – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Thomas Abeel – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
Electroencephalography (EEG) often relies on topographic scalp maps (topomaps) to visualize how biomarkers vary across the scalp. These visualizations can be generated many times during biomarker research, making higher efficiency pipelines important for reduced server load and latency. This research compares a raster based topomap rendering pipeline with a vector/SVG based pipeline in terms of server-side and client-side latency, and memory usage for EEG biomarker visualization.
A benchmark was implemented to measure the server-side cost of both pipelines over 100 iterations across 3 montage sizes and 5 interpolation resolutions using randomized EEG-like data. Within the tests, the vector pipeline was found to have server-side speedups between 2.88× and 5.29× while reducing memory usage between 1.24× and 1.42× dependent on the resolution. Stage-level analysis of the two pipelines showed that the raster pipeline was dominated by the rendering stage, whereas the vector pipeline distributed its cost mainly across interpolation and figure construction. However, improvements in server rendering came at the cost of client-side performance, with latency ratios ranging from 1.03× to 0.50× and memory-reduction ratios ranging from 0.96× to 0.14× depending on the resolution.
The results indicate that direct vector SVG rendering can significantly reduce server-side latency and memory usage. However, since the vector approach shifts part of the rendering work to the browser, the client impact remains an important concern. Overall, the proposed vector-based pipeline is a promising approach for modernizing EEG biomarker topomap visualization, but its benefits are dependent on its usage and the consideration of the client-side performance costs.