Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human‐in‐the‐loop software. (21st November 2022)

• Record Type: Journal Article
• Authors: Zhang, Zhen; Bi, Xiaoxue; Li, Pengcheng; Zhang, Chenglong; Yang, Yiming; Liu, Yu; Chen, Gang; Dong, Yuhui; Liu, Gongfa; Zhang, Yi
• Is Part Of: Journal of synchrotron radiation. Volume 30:Part 1(2023)
• Page Start: 169
• Page End: 178
• Publication Date: 2022-11-21
• Subjects: scanning tomography -- rotation‐axis alignment -- sample alignment -- genetic algorithms -- human‐in‐the‐loop -- computed tomography -- X‐ray microscopy; Synchrotron radiation -- Periodicals; Free electron lasers -- Periodicals; 539.73505
• DOI: 10.1107/S1600577522011067
• Languages: English
• ISSNs: 0909-0495

Abstract

Abstract : A highly automatic alignment scheme is proposed to address the pressing challenge in tomographic alignment of future scanning tomography experiments. The results show that the proposed method exhibits excellent sub‐pixel alignment accuracy and high time efficiency. Abstract : Tomography imaging methods at synchrotron light sources keep evolving, pushing multi‐modal characterization capabilities at high spatial and temporal resolutions. To achieve this goal, small probe size and multi‐dimensional scanning schemes are utilized more often in the beamlines, leading to rising complexities and challenges in the experimental setup process. To avoid spending a significant amount of human effort and beam time on aligning the X‐ray probe, sample and detector for data acquisition, most attention has been drawn to realigning the systems at the data processing stages. However, post‐processing cannot correct everything, and is not time efficient. Here we present automatic alignment schemes of the rotational axis and sample pre‐ and during the data acquisition process using a software approach which combines the advantages of genetic algorithms and human intelligence. Our approach shows excellent sub‐pixel alignment efficiency for both tasks in a short time, and therefore holds great potential for application in the data acquisition systems of future scanning tomography experiments.