用快速高斯点渲染技术，实现超声3D重建的实时化与高精度。
UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes
- 基于超声物理特性设计新型高斯点渲染框架
- 单卡5分钟完成重建，20分钟达0.99 SSIM
- 临床专家评测显示重建最真实，适合医疗影像应用
超声成像因安全、低成本和实时性被广泛应用，但其二维解读高度依赖操作者，导致结果差异大且认知负担重。2D到3D重建可提供标准化体积视图，缓解上述问题，但现有方法常计算成本高、内存占用大或不兼容超声物理特性。本文提出UltraGauss：首个针对超声的高斯点渲染框架，将视角合成技术扩展至超声波传播建模。不同于传统透视式点渲染，UltraGauss在3D中建模探头平面交线，符合声学成像原理。我们推导出适用于GPU并行化的高效光栅化边界公式，并引入数值稳定的协方差参数化，显著提升计算效率与重建精度。在真实临床超声数据上，UltraGauss在单个GPU上5分钟内达到当前最优重建效果，20分钟内SSIM达0.99。专家临床调研确认其重建结果在对比方法中最逼真。代码将在发表后开源。
原文摘要 · Abstract (English)
Ultrasound imaging is widely used due to its safety, affordability, and real-time capabilities, but its 2D interpretation is highly operator-dependent, leading to variability and increased cognitive demand. 2D-to-3D reconstruction mitigates these challenges by providing standardized volumetric views, yet existing methods are often computationally expensive, memory-intensive, or incompatible with ultrasound physics. We introduce UltraGauss: the first ultrasound-specific Gaussian Splatting framework, extending view synthesis techniques to ultrasound wave propagation. Unlike conventional perspective-based splatting, UltraGauss models probe-plane intersections in 3D, aligning with acoustic image formation. We derive an efficient rasterization boundary formulation for GPU parallelization and introduce a numerically stable covariance parametrization, improving computational efficiency and reconstruction accuracy. On real clinical ultrasound data, UltraGauss achieves state-of-the-art reconstructions in 5 minutes, and reaching 0.99 SSIM within 20 minutes on a single GPU. A survey of expert clinicians confirms UltraGauss' reconstructions are the most realistic among competing methods. Our CUDA implementation will be released upon publication.
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