Schertzer, JérémieMercier, CorentinRousseau, SylvainBoubekeur, TamyChaine, RaphaëlleKim, Min H.2022-04-222022-04-2220221467-8659https://doi.org/10.1111/cgf.14486https://diglib.eg.org:443/handle/10.1111/cgf14486We present a method to render massive brain tractograms in real time. Tractograms model the white matter architecture of the human brain using millions of 3D polylines (fibers), summing up to billions of segments. They are used by neurosurgeons before surgery as well as by researchers to better understand the brain. A typical raw dataset for a single brain represents dozens of gigabytes of data, preventing their interactive rendering.We address this challenge with a new GPU mesh shader pipeline based on a decomposition of the fiber set into compressed local representations that we call fiblets. Their spatial coherence is used at runtime to efficiently cull hidden geometry at the task shader stage while synthesizing the visible ones as polyline meshlets in a warp-scale parallel fashion at the mesh shader stage. As a result, our pipeline can feed a standard deferred shading engine to visualize the mesostructures of the brain with various classical rendering techniques, as well as simple interaction primitives. We demonstrate that our algorithm provides real-time framerates on very large tractograms that were out of reach for previous methods while offering a fiber-level granularity in both rendering and interaction.CCS Concepts: Hardware --> GPUs and Graphics Hardware; Rendering --> Real-Time Rendering; Visualization --> Medical ImagingHardwareGPUs and Graphics HardwareRenderingRealTime RenderingVisualizationMedical Imaging10.1111/cgf.14486447-46014 pages