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Mobile C-arm 3D Reconstruction in the Presence of Uncertain Geometry

  • Caleb Rottman
  • Lance McBride
  • Arvidas Cheryauka
  • Ross Whitaker
  • Sarang Joshi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9350)

Abstract

Computed tomography (CT) is a widely used medical technology. Adding 3D imaging to a mobile fluoroscopic C-arm reduces the cost of CT, as a mobile C-arm is much less expensive than a dedicated CT scanner. In this paper we explore the technical challenges to implementing 3D reconstruction on these devices. One of the biggest challenges is the problem of uncertain geometry; mobile C-arms do not have the same geometric consistency that exists in larger dedicated CT scanners. The geometric parameters of an acquisition scan are therefore uncertain, and a naïve reconstruction with these incorrect parameters leads to poor image quality. Our proposed method reconstructs the 3D image using the expectation maximization (EM) framework while jointly estimating the true geometry, thereby improving the feasibility of 3D imaging on mobile C-arms.

Keywords

Cone-beam reconstruction Expectation maximization Mobile C-arms 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Caleb Rottman
    • 1
  • Lance McBride
    • 2
  • Arvidas Cheryauka
    • 2
  • Ross Whitaker
    • 1
  • Sarang Joshi
    • 1
  1. 1.Scientific Computing and Imaging InstituteUniversity of UtahSalt Lake CityUSA
  2. 2.GE HealthcareSalt Lake CityUSA

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