FaCT-GS: Fast and Scalable CT Reconstruction with Gaussian Splatting

Gaussian Splatting (GS) has emerged as a dominating tech-nique for image rendering and has quickly been adapted for the X-ray Computed Tomography (CT) reconstruction task. However, despiteits growing popularity, the benefits of GS are typically not substantialenough to motivate a transition from well-established reconstruction al-gorithms. This paper addresses the most significant remaining limita-tions of the GS-based approach by introducing FaCT-GS, a frameworkfor fast and flexible CT reconstruction. Enabled by an in-depth optimiza-tion of the voxelization and rasterization pipelines, our new method issignificantly faster than its predecessors and scales well with projectionand output volume size. Furthermore, the improved voxelization enablesrapid fitting of Gaussians to pre-existing volumes, which can serve as aprior for warm-starting the reconstruction, or simply as an alternative,compressed representation. FaCT-GS is over 4× faster than the State ofthe Art GS CT reconstruction on standard 5122 projections, and over13× faster on 2k projections. Implementation and data available through:https://papieta.github.io/fact-gs/.