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

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

doi:10.1016/j.simpa.2023.100513

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

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

Ysgol Cyfrifiadureg a Pheirianneg

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

214 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

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.

Iaith wreiddiol	Saesneg
Rhif yr erthygl	100513
Cyfnodolyn	Software Impacts
Cyfrol	16
Dyddiad ar-lein cynnar	18 Mai 2023
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1016/j.simpa.2023.100513
Statws	Cyhoeddwyd - 22 Mai 2023

Mynediad at Ddogfen

10.1016/j.simpa.2023.100513Trwydded: CC BY

SIMPA_gvxrLlawysgrif awdur wedi’i dderbyn, 7.49 MB

1 Erthygl

Simulation of X-ray projections on GPU: benchmarking gVirtualXray with clinically realistic phantoms
Pointon, J., Wen, T., Tugwell-Allsup, J., Sujar, A., Létang, J. M. & Vidal, F., Meh 2023, Yn: Computer Methods and Programs in Biomedicine. 234, 107500.
Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

Mynediad agored
Ffeil
426 Wedi eu Llwytho i Lawr (Pure)

gVirtualXRay: an open source library from Bangor University to simulate X-ray images on GPU in real-time
Vidal, F. (Cyfranogwr)
Effaith: Technegol, Cymdeithasol

Dyfynnu hyn

@article{b421f4f68eef4d1a85d97acb78ffb7aa,

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

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. ",

keywords = "X-rays, Computed tomography, CT, GPU programming, Image registration, digitally reconstructed radiograph, DRR",

author = "Jamie Pointon and Tianci Wen and Jenna Tugwell-Allsup and L{\'e}tang, \{Jean Michel\} and Franck Vidal",

year = "2023",

month = may,

day = "22",

doi = "10.1016/j.simpa.2023.100513",

language = "English",

volume = "16",

journal = "Software Impacts",

issn = "2665-9638",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - gVirtualXray (gVXR): Simulating X-ray radiographs and CT volumes of anthropomorphic phantoms

AU - Pointon, Jamie

AU - Wen, Tianci

AU - Tugwell-Allsup, Jenna

AU - Létang, Jean Michel

AU - Vidal, Franck

PY - 2023/5/22

Y1 - 2023/5/22

N2 - 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.

AB - 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.

KW - X-rays

KW - Computed tomography

KW - CT

KW - GPU programming

KW - Image registration

KW - digitally reconstructed radiograph

KW - DRR

U2 - 10.1016/j.simpa.2023.100513

DO - 10.1016/j.simpa.2023.100513

M3 - Article

SN - 2665-9638

VL - 16

JO - Software Impacts

JF - Software Impacts

M1 - 100513

ER -

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

Crynodeb

Mynediad at Ddogfen

Ôl bys

Allbwn Ymchwil

Simulation of X-ray projections on GPU: benchmarking gVirtualXray with clinically realistic phantoms

Effeithiau

gVirtualXRay: an open source library from Bangor University to simulate X-ray images on GPU in real-time

Dyfynnu hyn