用B样条表示3D体积，实现高精度断层成像投影计算
SplineSplat: 3D Ray Tracing for Higher-Quality Tomography
- 基于移动B样条线性组合表示3D体积，结合神经网络加速射线积分
- 在无正则化条件下，重建质量优于传统体素方法
- 适用于需要高精度重建的医学或工业断层扫描场景
我们提出一种高效计算由平移B样条线性组合表示的3D体积的断层投影的方法。为此，设计了一种可处理任意投影几何的射线追踪算法，用于计算3D线积分。算法的核心组件是一个神经网络，能高效计算基函数的贡献。实验考虑了数据充分、无需正则化的适定情形，结果表明重建质量显著优于传统体素方法。
原文摘要 · Abstract (English)
We propose a method to efficiently compute tomographic projections of a 3D volume represented by a linear combination of shifted B-splines. To do so, we propose a ray-tracing algorithm that computes 3D line integrals with arbitrary projection geometries. One of the components of our algorithm is a neural network that computes the contribution of the basis functions efficiently. In our experiments, we consider well-posed cases where the data are sufficient for accurate reconstruction without the need for regularization. We achieve higher reconstruction quality than traditional voxel-based methods.
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