Elettra - Sincrotrone Trieste S.C.p.A, 34149 Basovizza, Trieste, Italy.
XGLab srl, Bruker Nano Analytics, 20134 Milan, Italy.
Sci Rep. 2020 Jun 19;10(1):9990. doi: 10.1038/s41598-020-66435-6.
X-Ray Fluorescence (XRF) scanning is a widespread technique of high importance and impact since it provides chemical composition maps crucial for several scientific investigations. There are continuous requirements for larger, faster and highly resolved acquisitions in order to study complex structures. Among the scientific applications that benefit from it, some of them, such as wide scale brain imaging, are prohibitively difficult due to time constraints. However, typically the overall XRF imaging performance is improving through technological progress on XRF detectors and X-ray sources. This paper suggests an additional approach where XRF scanning is performed in a sparse way by skipping specific points or by varying dynamically acquisition time or other scan settings in a conditional manner. This paves the way for Compressive Sensing in XRF scans where data are acquired in a reduced manner allowing for challenging experiments, currently not feasible with the traditional scanning strategies. A series of different compressive sensing strategies for dynamic scans are presented here. A proof of principle experiment was performed at the TwinMic beamline of Elettra synchrotron. The outcome demonstrates the potential of Compressive Sensing for dynamic scans, suggesting its use in challenging scientific experiments while proposing a technical solution for beamline acquisition software.
X 射线荧光（XRF）扫描是一种广泛应用的技术，具有重要意义和影响，因为它提供了对许多科学研究至关重要的化学成分图。为了研究复杂结构，人们不断需要更大、更快和更高分辨率的采集。在受益于它的科学应用中，有些应用，如大规模脑成像，由于时间限制而难以实现。然而，通常情况下，XRF 探测器和 X 射线源的技术进步正在提高整体 XRF 成像性能。本文提出了一种额外的方法，即通过跳过特定点或以有条件的方式动态改变采集时间或其他扫描设置来稀疏地进行 XRF 扫描。这为 XRF 扫描中的压缩感知铺平了道路，在这种情况下，数据以减少的方式采集，从而允许进行具有挑战性的实验，而这些实验目前使用传统的扫描策略是不可行的。本文提出了一系列用于动态扫描的不同压缩感知策略。在 Elettra 同步加速器的 TwinMic 光束线上进行了原理验证实验。实验结果证明了压缩感知在动态扫描中的潜力，表明其在具有挑战性的科学实验中的应用，并为光束线采集软件提出了一种技术解决方案。
