Treffer: X-ray simulations with gVXR in education, digital twining, experiment planning, and data analysis

Title:
X-ray simulations with gVXR in education, digital twining, experiment planning, and data analysis
Simulations RX avec gVXR pour l'éducation, le jumeau numérique, la planification expérimentale et l'analyse de données
Authors:
Vidal, Franck P., Afshari, Shaghayegh, Ahmed, Sharif, Albiol, Alberto, Albiol, Francisco, Béchet, Eric, Bellot, Alberto Corbí, Bosse, Stefan, Burkhard, Simon, Chahid, Younes, Chou, Cheng-Ying, Culver, Robert, Desbarats, Pascal, Dixon, Lewis, Friemann, Johan, Garbout, Amin, García-Lorenzo, Marcos, Giovannelli, Jean-François, Hanna, Ross, Hatton, Clémentine, Henry, Audrey, Kelly, Graham, Leblanc, Christophe, Leonardi, Alberto, Létang, Jean Michel, Lipscomb, Harry, Manchester, Tristan, Meere, Bas, Michelet, Claire, Middleburgh, Simon, Mihail, Radu P., Mitchell, Iwan, Perera, Liam, Puig, Martí, Racy, Malek, Rouwane, Ali, Seznec, Hervé, Sújar, Aaron, Tugwell-Allsup, Jenna, Villard, Pierre-Frédéric
Contributors:
A&M - Aérospatiale et Mécanique - ULiège
Source:
Nuclear Instruments and Methods in Physics Research. Section B, Beam Interactions with Materials and Atoms, 568, 165804 (2025-11)
Publisher Information:
Elsevier B.V., 2025.
Publication Year:
2025
Subject Terms:
Computed tomography, Digital twinning, GPU programming, Machine learning, Registration, Simulation, X-ray imaging, Graphic processor unit programming, Graphic processor units, Machine-learning, Real- time, X-ray computed tomography, Nuclear and High Energy Physics, Instrumentation, Engineering, computing & technology, Materials science & engineering, Ingénierie, informatique & technologie, Science des matériaux & ingénierie
Document Type:
Fachzeitschrift journal article<br />http://purl.org/coar/resource_type/c_6501<br />article<br />peer reviewed
Language:
English
Relation:
https://www.sciencedirect.com/science/article/pii/S0168583X25001946?via%3Dihub; urn:issn:0168-583X; urn:issn:1872-9584
DOI:
10.1016/j.nimb.2025.165804
Access URL:
https://orbi.uliege.be/handle/2268/336219
Rights:
open access
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
Accession Number:
edsorb.336219
Database:
ORBi

Weitere Informationen

gVirtualXray (gVXR) is an open-source framework that relies on the Beer–Lambert law to simulate X-ray images in real time on a graphics processor unit (GPU) using triangular meshes. A wide range of programming languages is supported (C/C++, Python, R, Ruby, Tcl, C#, Java, and GNU Octave). Simulations generated with gVXR have been benchmarked with clinically realistic phantoms (i.e. complex structures and materials) using Monte Carlo (MC) simulations, real radiographs and real digitally reconstructed radiographs (DRRs), and X-ray computed tomography (XCT). It has been used in a wide range of applications, including real-time medical simulators, proposing a new densitometric radiographic modality in clinical imaging, studying noise removal techniques in fluoroscopy, teaching particle physics and X-ray imaging to undergraduate students in engineering, and XCT to masters students, predicting image quality and artifacts in material science, etc. gVXR has also been used to produce a high number of realistic simulated images in optimisation problems and to train machine learning algorithms. This paper presents a comprehensive review of such applications of gVXR.