Phantom task-based image quality assessment of three generations of rapid kV-switching dual-energy CT systems on virtual monoenergetic images.
deep learning image reconstruction
dual-energy
iterative reconstruction
multidetector computed tomography
task-based image quality assessment
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Apr 2022
Apr 2022
Historique:
revised:
11
02
2022
received:
09
11
2021
accepted:
11
02
2022
pubmed:
21
2
2022
medline:
14
4
2022
entrez:
20
2
2022
Statut:
ppublish
Résumé
To compare the spectral performance of three rapid kV switching dual-energy CT (DECT) systems on virtual monoenergetic images (VMIs) at low-energy levels on abdominal imaging. A multi-energy phantom was scanned on three DECT systems equipped with three different gemstone spectral imaging (GSI) platforms: GSI (1st generation, GSI-1st), GSI-Pro (2nd generation, GSI-2nd ), and GSI-Xtream (3rd generation, GSI-3rd). Acquisitions on the phantom were performed with a CTDI For all GSI platforms, the noise magnitude decreased from 40 to 70 keV, and using AV50 compared to FBP. The average NPS spatial frequency (f Differences in image quality were found between the GSI platforms for VMIs at low keV. The new DLR algorithm on the GSI-3rd platform reduced noise and improved spatial resolution and detectability without changing the noise texture for VMIs at low keV. The choice of the best energy level in VMIs depends on the platform and the reconstruction algorithm.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2233-2244Informations de copyright
© 2022 American Association of Physicists in Medicine.
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