gVirtualXray (gVXR): Simulating X-ray radiographs and CT volumes of anthropomorphic phantoms

Jamie Pointon, Tianci Wen, Jenna Tugwell-Allsup, Jean Michel Létang, Franck Vidal

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Abstract

gVirtualXray (gVXR) is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in realtime on a graphics processor unit (GPU) using triangular meshes. We produced four Jupyter Notebooks to compare images simulated with gVXR and ground truth image of an anthropomorphic phantom: (i) an X-ray projection generated using a Monte Carlo simulation code, (ii) real digitally reconstructed radiographs (DRRs), (iii) computed tomography (CT) slices, and (iv) a real radiograph acquired with a clinical X-ray imaging system. Image registration was deployed in two Notebooks to align the simulated image on the corresponding ground truth image. We demonstrated that accurate images can be generated in milliseconds with gVirtualXray when scattering can be ignored.
Original languageEnglish
Article number100513
JournalSoftware Impacts
Volume16
Early online date18 May 2023
DOIs
Publication statusPublished - 22 May 2023

Keywords

  • X-rays
  • Computed tomography
  • CT
  • GPU programming
  • Image registration
  • digitally reconstructed radiograph
  • DRR

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