IDEAS home Printed from https://ideas.repec.org/a/bpj/mcmeap/v28y2022i3p269-278n7.html
   My bibliography  Save this article

Monte Carlo simulation of sensitivity functions for few-view computed tomography of strongly absorbing media

Author

Listed:
  • Konovalov Alexander

    (Computational Center, Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All–Russia Research Institute of Technical Physics”, Snezhinsk, Chelyabinsk Region, 456770, Russia)

  • Vlasov Vitaly
  • Kolchugin Sergey

    (Computational Center, Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All–Russia Research Institute of Technical Physics”, Snezhinsk, Chelyabinsk Region, 456770, Russia)

  • Malyshkin Gennady
  • Mukhamadiyev Rim

    (Department of Mathematics, Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All–Russia Research Institute of Technical Physics”, Snezhinsk, Chelyabinsk Region, 456770, Russia)

Abstract

The paper describes a sensitivity function calculation method for few-view X-ray computed tomography of strongly absorbing objects. It is based on a probabilistic interpretation of energy transport through the object from a source to a detector. A PRIZMA code package is used to track photons. The code is developed at FSUE “RFNC–VNIITF named after Academ. E. I. Zababakhin” and implements a stochastic Monte Carlo method. The value of the sensitivity function in a discrete cell of the reconstruction region is assumed to be directly proportional to the fraction of photon trajectories which cross the cell from all those recorded by the detector. The method’s efficiency is validated through a numerical experiment on the reconstruction of a section of a spherical heavy-metal phantom with an air cavity and a density difference of 25 Ṫhe proposed method is shown to outperform the method based on projection approximation in case of reconstruction from 9 views.

Suggested Citation

  • Konovalov Alexander & Vlasov Vitaly & Kolchugin Sergey & Malyshkin Gennady & Mukhamadiyev Rim, 2022. "Monte Carlo simulation of sensitivity functions for few-view computed tomography of strongly absorbing media," Monte Carlo Methods and Applications, De Gruyter, vol. 28(3), pages 269-278, September.
    • Handle: RePEc:bpj:mcmeap:v:28:y:2022:i:3:p:269-278:n:7
    DOI: 10.1515/mcma-2022-2120
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/mcma-2022-2120
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/mcma-2022-2120?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:bpj:mcmeap:v:28:y:2022:i:3:p:269-278:n:7. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    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.