Title: Rapidly-converging multigrid reconstruction of cone-beam tomographic data Show Chinese title

Title: 快速收敛的锥束断层扫描数据多网格重建

Abstract: In the context of large-angle cone-beam tomography (CBCT), we present a practical iterative reconstruction (IR) scheme designed for rapid convergence as required for large datasets. The robustness of the reconstruction is provided by the "space-filling" source trajectory along which the experimental data is collected. The speed of convergence is achieved by leveraging the highly isotropic nature of this trajectory to design an approximate deconvolution filter that serves as a pre-conditioner in a multi-grid scheme. We demonstrate this IR scheme for CBCT and compare convergence to that of more traditional techniques. Show Chinese abstract

Abstract: 在大角度锥束断层扫描（CBCT）的背景下，我们提出了一种实用的迭代重建（IR）方案，该方案旨在实现快速收敛，以满足大数据集的需求。 重建的鲁棒性由沿“填充空间”源轨迹收集的实验数据提供。 通过利用该轨迹的高度各向同性特性，设计了一个近似去卷积滤波器，作为多网格方案中的预条件器，从而实现了快速收敛。 我们展示了该IR方案在CBCT中的应用，并将其收敛性与更传统的技术进行了比较。