X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development

Franck P. Vidal; Shaghayegh Afshari; Sharif Ahmed; Carolyn Atkins; Éric Béchet; Alberto Corbí Bellot; Stefan Bosse; Younes Chahid; Cheng Ying Chou; Robert Culver; Lewis Dixon; Johan Friemann; Amin Garbout; Clémentine Hatton; Audrey Henry; Christophe Leblanc; Alberto Leonardi; Jean Michel Létang; Harry Lipscomb; Tristan Manchester; Bas Meere; Simon Middleburgh; Iwan Mitchell; Liam Perera; Martí Puig; Jenna Tugwell-Allsup

doi:10.1117/12.3025315

X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development

Franck P. Vidal (Corresponding author)
, Shaghayegh Afshari
, Sharif Ahmed
, Carolyn Atkins
, Éric Béchet
, Alberto Corbí Bellot
, Stefan Bosse
, Younes Chahid
, Cheng Ying Chou
, Robert Culver
, Lewis Dixon
, Johan Friemann
, Amin Garbout
, Clémentine Hatton
, Audrey Henry
, Christophe Leblanc
, Alberto Leonardi
, Jean Michel Létang
, Harry Lipscomb
, Tristan Manchester

Bas Meere, Simon Middleburgh, Iwan Mitchell, Liam Perera, Martí Puig, Jenna Tugwell-Allsup

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

1 Downloads (Pure)

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 (CT). 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 optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.

Original language	English
Title of host publication	Developments in X-Ray Tomography XV
Editors	Bert Muller, Ge Wang
Publisher	SPIE
Number of pages	20
ISBN (Electronic)	9781510679658
ISBN (Print)	9781510679641
DOIs	https://doi.org/10.1117/12.3025315
Publication status	Published - 23 Oct 2024
Event	15th SPIE Conference on Developments in X-Ray Tomography - San Diego, United States Duration: 19 Aug 2024 → 22 Aug 2024

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	13152
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	15th SPIE Conference on Developments in X-Ray Tomography
Country/Territory	United States
City	San Diego
Period	19/08/24 → 22/08/24

Bibliographical note

Publisher Copyright:
© 2024 SPIE.

Keywords

Computed tomography
Digital twinning
GPU programming
Simulation
X-ray imaging

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10.1117/12.3025315

pdfFinal published version, 15.9 MBLicence: TAVERNE

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Vidal, F. P., Afshari, S., Ahmed, S., Atkins, C., Béchet, É., Bellot, A. C., Bosse, S., Chahid, Y., Chou, C. Y., Culver, R., Dixon, L., Friemann, J., Garbout, A., Hatton, C., Henry, A., Leblanc, C., Leonardi, A., Létang, J. M., Lipscomb, H., ... Tugwell-Allsup, J. (2024). X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development. In B. Muller, & G. Wang (Eds.), Developments in X-Ray Tomography XV Article 131520W (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 13152). SPIE. https://doi.org/10.1117/12.3025315

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title = "X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development",

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 (CT). 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 optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.",

keywords = "Computed tomography, Digital twinning, GPU programming, Simulation, X-ray imaging",

author = "Vidal, \{Franck P.\} and Shaghayegh Afshari and Sharif Ahmed and Carolyn Atkins and {\'E}ric B{\'e}chet and Bellot, \{Alberto Corb{\'i}\} and Stefan Bosse and Younes Chahid and Chou, \{Cheng Ying\} and Robert Culver and Lewis Dixon and Johan Friemann and Amin Garbout and Cl{\'e}mentine Hatton and Audrey Henry and Christophe Leblanc and Alberto Leonardi and L{\'e}tang, \{Jean Michel\} and Harry Lipscomb and Tristan Manchester and Bas Meere and Simon Middleburgh and Iwan Mitchell and Liam Perera and Mart{\'i} Puig and Jenna Tugwell-Allsup",

note = "Publisher Copyright: {\textcopyright} 2024 SPIE.; 15th SPIE Conference on Developments in X-Ray Tomography ; Conference date: 19-08-2024 Through 22-08-2024",

year = "2024",

month = oct,

day = "23",

doi = "10.1117/12.3025315",

language = "English",

isbn = "9781510679641",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Bert Muller and Ge Wang",

booktitle = "Developments in X-Ray Tomography XV",

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}

Vidal, FP, Afshari, S, Ahmed, S, Atkins, C, Béchet, É, Bellot, AC, Bosse, S, Chahid, Y, Chou, CY, Culver, R, Dixon, L, Friemann, J, Garbout, A, Hatton, C, Henry, A, Leblanc, C, Leonardi, A, Létang, JM, Lipscomb, H, Manchester, T, Meere, B, Middleburgh, S, Mitchell, I, Perera, L, Puig, M & Tugwell-Allsup, J 2024, X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development. in B Muller & G Wang (eds), Developments in X-Ray Tomography XV., 131520W, Proceedings of SPIE - The International Society for Optical Engineering, vol. 13152, SPIE, 15th SPIE Conference on Developments in X-Ray Tomography, San Diego, United States, 19/08/24. https://doi.org/10.1117/12.3025315

X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development. / Vidal, Franck P. (Corresponding author); Afshari, Shaghayegh; Ahmed, Sharif et al.
Developments in X-Ray Tomography XV. ed. / Bert Muller; Ge Wang. SPIE, 2024. 131520W (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 13152).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development

AU - Vidal, Franck P.

AU - Afshari, Shaghayegh

AU - Ahmed, Sharif

AU - Atkins, Carolyn

AU - Béchet, Éric

AU - Bellot, Alberto Corbí

AU - Bosse, Stefan

AU - Chahid, Younes

AU - Chou, Cheng Ying

AU - Culver, Robert

AU - Dixon, Lewis

AU - Friemann, Johan

AU - Garbout, Amin

AU - Hatton, Clémentine

AU - Henry, Audrey

AU - Leblanc, Christophe

AU - Leonardi, Alberto

AU - Létang, Jean Michel

AU - Lipscomb, Harry

AU - Manchester, Tristan

AU - Meere, Bas

AU - Middleburgh, Simon

AU - Mitchell, Iwan

AU - Perera, Liam

AU - Puig, Martí

AU - Tugwell-Allsup, Jenna

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N2 - 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 (CT). 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 optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.

AB - 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 (CT). 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 optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT.

KW - Computed tomography

KW - Digital twinning

KW - GPU programming

KW - Simulation

KW - X-ray imaging

UR - https://www.scopus.com/pages/publications/85212510070

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DO - 10.1117/12.3025315

M3 - Conference contribution

AN - SCOPUS:85212510070

SN - 9781510679641

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Developments in X-Ray Tomography XV

A2 - Muller, Bert

A2 - Wang, Ge

PB - SPIE

T2 - 15th SPIE Conference on Developments in X-Ray Tomography

Y2 - 19 August 2024 through 22 August 2024

ER -

Vidal FP, Afshari S, Ahmed S, Atkins C, Béchet É, Bellot AC et al. X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development. In Muller B, Wang G, editors, Developments in X-Ray Tomography XV. SPIE. 2024. 131520W. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.3025315

X-ray simulations with gVXR as a useful tool for education, data analysis, set-up of CT scans, and scanner development

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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