Parallel Iterative Methods with A Priori Information for Robust Computed Laminography of Low Contrast, Difficult-To-Measure Objects

该项目的目标是开发一种新的3D断层重建方法，使计算机断层扫描（CL）成为一种可行的技术，用于无损检测方案，其中标准计算机断层扫描（CT）产生不满意的结果，例如多层印刷电路板的检测，纤维增强塑料的层结构分析，或用于轻质结构的大型笨重组件的检测。为了提高重建的质量和性能的每一个方面的管道从校准的扫描仪的数学建模，以快速并行算法在现代硬件上必须加以解决。我们专注于四个关键的研究领域：1）在整个重建管道的先验信息的一致使用，2）基函数和迭代收敛标准的优化，3）通过利用新的并行硬件架构，减少重建时间和资源的使用，和4）强大和有效的数据采集例程的校准。这种跨学科的全流程优化需要来自数学、计算机科学和工程领域的研究人员的合作。

The goal of this project is to develop a novel 3D tomographic reconstruction method to make computed laminography (CL) a viable technique for non-destructive inspection scenarios, where standard computed tomography (CT) yields unsatisfying results, for example inspection of multilayered printed circuit boards, layer structure analysis of fibre-reinforced plastic, or inspection of large unwieldy components used in lightweight construction. To improve the reconstruction quality and performance every aspect of the pipeline from calibration of the scanner over the mathematical modelling to fast parallel algorithms on modern hardware has to be addressed. We focus on four key research areas: 1) consistent use of a priori information across the whole reconstruction pipeline, 2) optimization of basis functions and iterative convergence criteria, 3) reduction of the reconstruction time and resource usage by utilizing novel parallel hardware architectures, and 4) robust and efficient calibration of the data acquisition routines. Such a cross-disciplinary, whole-pipeline optimization requires the cooperation of researchers from the fields of mathematics, computer science, and engineering.