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Automatic synchrotron tomographic alignment schemes based on genetic algorithms and human-in-the-loop software

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...

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Detalles Bibliográficos
Autores principales: Zhang, Zhen, Bi, Xiaoxue, Li, Pengcheng, Zhang, Chenglong, Yang, Yiming, Liu, Yu, Chen, Gang, Dong, Yuhui, Liu, Gongfa, Zhang, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Union of Crystallography 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814067/
https://www.ncbi.nlm.nih.gov/pubmed/36601935
http://dx.doi.org/10.1107/S1600577522011067
Descripción
Sumario: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.