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.
@article{arxiv.2511.11078,
title = {SplineSplat: 3D Ray Tracing for Higher-Quality Tomography},
author = {Youssef Haouchat and Sepand Kashani and Aleix Boquet-Pujadas and Philippe Thévenaz and Michael Unser},
journal= {arXiv preprint arXiv:2511.11078},
year = {2025}
}