Systematic analysis of bias and variability of texture measurements in computed tomography.
computed tomography
quantitative
radiomics
simulation
texture analysis
tumor
Journal
Journal of medical imaging (Bellingham, Wash.)
ISSN: 2329-4302
Titre abrégé: J Med Imaging (Bellingham)
Pays: United States
ID NLM: 101643461
Informations de publication
Date de publication:
Jul 2019
Jul 2019
Historique:
received:
20
10
2018
accepted:
18
06
2019
entrez:
25
7
2019
pubmed:
25
7
2019
medline:
25
7
2019
Statut:
ppublish
Résumé
Texture is a key radiomics measurement for quantification of disease and disease progression. The sensitivity of the measurements to image acquisition, however, is uncertain. We assessed bias and variability of computed tomography (CT) texture feature measurements across many clinical image acquisition settings and reconstruction algorithms. Diverse, anatomically informed textures (texture A, B, and C) were simulated across 1188 clinically relevant CT imaging conditions representing four in-plane pixel sizes (0.4, 0.5, 0.7, and 0.9 mm), three slice thicknesses (0.625, 1.25, and 2.5 mm), three dose levels (
Identifiants
pubmed: 31338387
doi: 10.1117/1.JMI.6.3.033503
pii: 18235RR
pmc: PMC6625670
doi:
Types de publication
Journal Article
Langues
eng
Pagination
033503Subventions
Organisme : NHLBI NIH HHS
ID : HHSN268201500021C
Pays : United States
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