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Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human-in-the-loop software
oleh: Zhen Zhang, Xiaoxue Bi, Pengcheng Li, Chenglong Zhang, Yiming Yang, Yu Liu, Gang Chen, Yuhui Dong, Gongfa Liu, Yi Zhang
| Format: | Article |
|---|---|
| Diterbitkan: | International Union of Crystallography 2023-01-01 |
Deskripsi
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.