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Instruments / Technical Area	Publication Details	Published	Actions
DIAD-Dual Imaging and Diffraction Beamline I12-JEEP: Joint Engineering, Environmental and Processing	X-ray simulations with gVXR in education, digital twining, experiment planning, and data analysis Franck P. Vidal , Shaghayegh Afshari , Sharif Ahmed , Alberto Albiol , Francisco Albiol , Éric Béchet , Alberto Corbí Bellot , Stefan Bosse , Simon Burkhard , Younes Chahid , Cheng-Ying Chou , Robert Culver , Pascal Desbarats , Lewis Dixon , Johan Friemann , Amin Garbout , Marcos García-Lorenzo , Jean-François Giovannelli , Ross Hanna , Clémentine Hatton , Audrey Henry , Graham Kelly , Christophe Leblanc , Alberto Leonardi , Jean Michel Létang , Harry Lipscomb , Tristan Manchester , Bas Meere , Claire Michelet , Simon Middleburgh , Radu P. Mihail , Iwan Mitchell , Liam Perera , Martí Puig , Malek Racy , Ali Rouwane , Hervé Seznec , Aaron Sújar , Jenna Tugwell-Allsup , Pierre-Frédéric Villard Nuclear Instruments And Methods In Physics Research Section B: Beam Interactions With Materials And Atoms 568 DOI: 10.1016/j.nimb.2025.165804 Diamond Proposal Number(s): [29820] Open Access Show Abstract ▼ Abstract: 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.	Nov 2025

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DIAD-Dual Imaging and Diffraction Beamline
I12-JEEP: Joint Engineering, Environmental and Processing

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