Deep learning-based coronary artery motion estimation and compensation for short-scan cardiac CT.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: During a typical cardiac short scan, the heart can move several millimeters. As a result, the corresponding CT reconstructions may be corrupted by motion artifacts. Especially the assessment of small structures, such as the coronary arteries, is potentially impaired by the presence of these artifacts. In order to estimate and compensate for coronary artery motion, this manuscript proposes the deep partial angle-based motion compensation (Deep PAMoCo).

Authors

  • Joscha Maier
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Sergej Lebedev
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Julien Erath
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Elias Eulig
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Stefan Sawall
    German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Eric Fournié
    Siemens Healthineers, Forchheim, Germany.
  • Karl Stierstorfer
    Siemens Healthineers, Forchheim, Germany.
  • Michael Lell
    University Hospital Nürnberg, Nürnberg, 90419, Germany.
  • Marc Kachelrieß
    German Cancer Research Center, Heidelberg, 69120, Germany.