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

arXiv: https://arxiv.org/abs/2604.01844 · HTML: https://mlsanity.com/paper/2604.01844/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 80 references that are in the map.
- First posted on arXiv 2 Apr 2026.

## Builds on (most cited first, 4 of 4)

- [A large annotated medical image dataset for the development and evaluation of segmentation algorithms](https://mlsanity.com/paper/1902.09063/) (2019)
- [DISTWAR: Fast Differentiable Rendering on Raster-based Rendering Pipelines](https://mlsanity.com/paper/2401.05345/) (2023)
- [Faster-GS: Analyzing and Improving Gaussian Splatting Optimization](https://mlsanity.com/paper/2602.09999/) (2026)
- [X-Field: A Physically Grounded Representation for 3D X-ray Reconstruction](https://mlsanity.com/paper/2503.08596/) (2025)

## Built on by (most cited first, 2 of 2)

- [X-Splat: Gaussian Splatting for 3D CBCT Generation from Single Panoramic Radiograph](https://mlsanity.com/paper/2607.02099/) (2026)
- [Gaussian Material Fields for Volumetric Multi-Energy CT Decomposition](https://mlsanity.com/paper/2610.09492/) (2026)

## Abstract (arXiv)

Gaussian Splatting (GS) has emerged as a dominating technique for image rendering and has quickly been adapted for the X-ray Computed Tomography (CT) reconstruction task. However, despite its growing popularity, the benefits of GS are typically not substantial enough to motivate a transition from well-established reconstruction algorithms. This paper addresses the most significant remaining limitations of the GS-based approach by introducing FaCT-GS, a framework for fast and flexible CT reconstruction. Enabled by an in-depth optimization of the voxelization and rasterization pipelines, our new method is significantly faster than its predecessors and scales well with projection and output volume size. Furthermore, the improved voxelization enables rapid fitting of Gaussians to pre-existing volumes, which can serve as a prior for warm-starting the reconstruction, or simply as an alternative, compressed representation. FaCT-GS is over 4X faster than the State of the Art GS CT reconstruction on standard 512x512 projections, and over 13X faster on 2k projections. Implementation and data available through: https://github.com/PaPieta/fact-gs.