用可裁剪的高斯点云实现实时电影级医学影像可视化
ClipGS: Clippable Gaussian Splatting for Interactive Cinematic Visualization of Volumetric Medical Data
- 引入可调节裁剪平面的高斯点云框架，动态控制显示范围
- 实现平均36.635 PSNR画质、156 FPS实时渲染和16.1 MB模型大小
- 适合需要交互式医学影像展示的临床诊断与手术规划场景
体积医学数据的可视化对提升诊断准确性、优化手术规划与医学教育至关重要。电影级渲染技术通过呈现复杂的解剖细节，显著增强医疗理解与决策能力。然而，高昂的计算成本和低渲染速度限制了其在实际应用中的交互性。本文提出ClipGS，一种支持裁剪平面的创新高斯点云框架，用于体积医学数据的交互式电影级可视化。为应对动态交互挑战，我们设计了一种可学习的截断机制，自动根据裁剪平面调整高斯原语的可见性；同时引入自适应调整模型，动态优化高斯变形以提升渲染质量。我们在五组体积医学数据（包括CT与解剖切片数据）上验证方法，达到平均36.635 PSNR画质、156 FPS渲染速度及16.1 MB模型尺寸，优于当前最优方法的渲染质量与效率。
原文摘要 · Abstract (English)
The visualization of volumetric medical data is crucial for enhancing diagnostic accuracy and improving surgical planning and education. Cinematic rendering techniques significantly enrich this process by providing high-quality visualizations that convey intricate anatomical details, thereby facilitating better understanding and decision-making in medical contexts. However, the high computing cost and low rendering speed limit the requirement of interactive visualization in practical applications. In this paper, we introduce ClipGS, an innovative Gaussian splatting framework with the clipping plane supported, for interactive cinematic visualization of volumetric medical data. To address the challenges posed by dynamic interactions, we propose a learnable truncation scheme that automatically adjusts the visibility of Gaussian primitives in response to the clipping plane. Besides, we also design an adaptive adjustment model to dynamically adjust the deformation of Gaussians and refine the rendering performance. We validate our method on five volumetric medical data (including CT and anatomical slice data), and reach an average 36.635 PSNR rendering quality with 156 FPS and 16.1 MB model size, outperforming state-of-the-art methods in rendering quality and efficiency.
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