用于实时应用的张量断层扫描X射线散射数据的快速重建
Fast reconstruction of tensor tomographic X-ray scattering data for real-time applications
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中文总结 AI 辅助
研究针对X射线散射张量断层扫描重建慢限制实时应用的问题，引入扩展的直接重建方法，通过特定步骤计算代数滤波器，经模拟和实验验证，该方法能大幅减少计算时间，实现快速重建，为实时散射成像等应用提供可能。
中文摘要 AI 辅助
X射线散射张量断层扫描可揭示三维纳米级结构取向，但其对缓慢迭代重建的依赖限制了实时应用。我们引入了一种适用于平行光束几何结构的直接重建方法的扩展，通过单个滤波和反投影步骤计算近似多次迭代更新的代数滤波器。该方法通过明确分离断层投影仪和视相关混合算子，可推广到张量表示和（小角）X射线散射测量模式。模拟和实验结果表明，该方法在减少计算时间一个数量级以上的同时近似迭代重建，在商用硬件上1秒内可实现53x53x53x28张量体积的重建。由此产生的速度和稳定性实现了高通量分析，并为基于散射的实时成像打开了大门。
英文摘要
X-ray scattering tensor tomography reveals nanoscale structural orientation in 3D, but its reliance on slow iterative reconstruction limits real-time use. We introduce an extension of a direct reconstruction approach for parallel-beam geometries that computes algebraic filters approximating multiple iterative updates with a single filtering and back-projection step. By explicitly separating the tomographic projector from a view-dependent mixing operator, the method generalizes across tensor representations and modes of (small-angle) X-ray scattering measurement. Simulated and experimental results show that the approach approximates iterative reconstructions while reducing computation time by over an order of magnitude, realizing a reconstruction of a 53x53x53x28 tensor volume in 1 second on commercially-available hardware. The resulting speed and stability enable high-throughput analysis and open the door to real-time scattering-based imaging.
