IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0141682.html
   My bibliography  Save this article

Analysis and Correction of Dynamic Geometric Misalignment for Nano-Scale Computed Tomography at BSRF

Author

Listed:
  • Jian Fu
  • Chen Li
  • Zhenzhong Liu

Abstract

Due to its high spatial resolution, synchrotron radiation x-ray nano-scale computed tomography (nano-CT) is sensitive to misalignments in scanning geometry, which occurs quite frequently because of mechanical errors in manufacturing and assembly or from thermal expansion during the time-consuming scanning. Misalignments degrade the imaging results by imposing artifacts on the nano-CT slices. In this paper, the geometric misalignment of the synchrotron radiation nano-CT has been analyzed by partial derivatives on the CT reconstruction algorithm and a correction method, based on cross correlation and least-square sinusoidal fitting, has been reported. This work comprises a numerical study of the method and its experimental verification using a dataset measured with the full-field transmission x-ray microscope nano-CT at the beamline 4W1A of the Beijing Synchrotron Radiation Facility. The numerical and experimental results have demonstrated the validity of the proposed approach. It can be applied for dynamic geometric misalignment and needs neither phantom nor additional correction scanning. We expect that this method will simplify the experimental operation of synchrotron radiation nano-CT.

Suggested Citation

  • Jian Fu & Chen Li & Zhenzhong Liu, 2015. "Analysis and Correction of Dynamic Geometric Misalignment for Nano-Scale Computed Tomography at BSRF," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-17, October.
  • Handle: RePEc:plo:pone00:0141682
    DOI: 10.1371/journal.pone.0141682
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0141682
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0141682&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0141682?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jian Fu & Zhenzhong Liu & Jingzheng Wang, 2016. "Multi-Mounted X-Ray Computed Tomography," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-15, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0141682. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.