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

Konovalov Alexander (), Vlasov Vitaly (), Kolchugin Sergey (), Malyshkin Gennady () and Mukhamadiyev Rim ()
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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: Computational Center, Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All–Russia Research Institute of Technical Physics”, Snezhinsk, Chelyabinsk Region, 456770, Russia
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: Department of Mathematics, Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All–Russia Research Institute of Technical Physics”, Snezhinsk, Chelyabinsk Region, 456770, Russia
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

Monte Carlo Methods and Applications, 2022, vol. 28, issue 3, 269-278

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.

Keywords: Few-view X-ray computed tomography (FVCT); strongly absorbing object; sensitivity function; PRIZMA code package; Monte Carlo method; adaptive smoothing; reconstruction algorithm (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/mcma-2022-2120

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