用高斯点云加速CT重建，速度比当前最快方法快13倍。
FaCT-GS: Fast and Scalable CT Reconstruction with Gaussian Splatting
- 优化体素化与光栅化流程，提升重建效率。
- 512×512投影下速度超现有方法4倍，2048×2048下超13倍。
- 支持快速初始化，适合需快速重建的医学影像场景。
高斯点云（Gaussian Splatting, GS）已发展为图像渲染主流技术，并被迅速应用于X射线计算机断层扫描（CT）重建。然而，尽管其应用日益广泛，现有GS方法在性能提升上仍不足以推动从成熟重建算法的迁移。本文提出FaCT-GS，一种快速且可扩展的CT重建框架。通过深度优化体素化与光栅化管线，新方法显著提升速度，并在投影和输出体积增大时保持良好扩展性。改进的体素化支持对已有体积快速拟合高斯点，可用作重建的初始先验，或作为压缩表示替代。在标准512×512投影下，FaCT-GS速度超过现有最先进方法4倍；在2048×2048投影下，速度提升超13倍。代码与数据已开源：https://github.com/PaPieta/fact-gs。
原文摘要 · Abstract (English)
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.
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