A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder

Brent van der Heyden, Martin Uray, Gabriel Paiva Fonseca, Philipp Huber, Defne Us, Ivan Messner, Adam Law, Anastasiia Parii, Niklas Reisz, Ilaria Rinaldi, Gloria Vilches Freixas, Heinz Deutschmann, Frank Verhaegen, Philipp Steininger*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Original languageEnglish
Article number145002
Number of pages16
JournalPhysics in Medicine and Biology
Volume65
Issue number14
DOIs
Publication statusPublished - 21 Jul 2020

Keywords

  • cone-beam CT
  • artificial intelligence
  • scatter removal
  • scatter prediction
  • Monte Carlo
  • PROTON DOSE CALCULATION
  • FLAT-PANEL IMAGER
  • X-RAY TUBE
  • COMPUTED-TOMOGRAPHY
  • GENERAL FRAMEWORK
  • MOTION ARTIFACTS
  • CBCT
  • HEAD
  • FEASIBILITY
  • RADIATION

Cite this

van der Heyden, B., Uray, M., Fonseca, G. P., Huber, P., Us, D., Messner, I., Law, A., Parii, A., Reisz, N., Rinaldi, I., Freixas, G. V., Deutschmann, H., Verhaegen, F., & Steininger, P. (2020). A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder. Physics in Medicine and Biology, 65(14), [145002]. https://doi.org/10.1088/1361-6560/ab8954