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X-Ray Computed Tomography Through Scatter

  • Adam Geva
  • Yoav Y. SchechnerEmail author
  • Yonatan Chernyak
  • Rajiv Gupta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11218)

Abstract

In current Xray CT scanners, tomographic reconstruction relies only on directly transmitted photons. The models used for reconstruction have regarded photons scattered by the body as noise or disturbance to be disposed of, either by acquisition hardware (an anti-scatter grid) or by the reconstruction software. This increases the radiation dose delivered to the patient. Treating these scattered photons as a source of information, we solve an inverse problem based on a 3D radiative transfer model that includes both elastic (Rayleigh) and inelastic (Compton) scattering. We further present ways to make the solution numerically efficient. The resulting tomographic reconstruction is more accurate than traditional CT, while enabling significant dose reduction and chemical decomposition. Demonstrations include both simulations based on a standard medical phantom and a real scattering tomography experiment.

Keywords

CT Xray Inverse problem Elastic/inelastic scattering 

Notes

Acknowledgments

We thank V. Holodovsky, A. Levis, M. Sheinin, A. Kadambi, O. Amit, Y. Weissler for fruitful discussions, A. Cramer, W. Krull, D. Wu, J. Hecla, T. Moulton, and K. Gendreau for engineering the static CT scanner prototype, and I. Talmon and J. Erez for technical support. YYS is a Landau Fellow - supported by the Taub Foundation. His work is conducted in the Ollendorff Minerva Center. Minerva is funded by the BMBF. This research was supported by the Israeli Ministry of Science, Technology and Space (Grant 3-12478). RG research was partially supported by the following grants: Air Force Contract Number FA8650-17-C-9113; US Army USAMRAA Joint Warfighter Medical Research Program, Contract No. W81XWH-15-C-0052; Congressionally Directed Medical Research Program W81XWH-13-2-0067.

Supplementary material

474202_1_En_3_MOESM1_ESM.pdf (633 kb)
Supplementary material 1 (pdf 632 KB)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Adam Geva
    • 1
  • Yoav Y. Schechner
    • 1
    Email author
  • Yonatan Chernyak
    • 1
  • Rajiv Gupta
    • 2
  1. 1.Viterbi Faculty of Electrical EngineeringTechnion - Israel Institute of TechnologyHaifaIsrael
  2. 2.Massachusetts General HospitalHarvard Medical SchoolBostonUSA

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