Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis
Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis
About this item
Full title
Author / Creator
Zhang, Gumuyang , Zhang, Xiaoxiao , Xu, Lili , Bai, Xin , Jin, Ru , Xu, Min , Yan, Jing , Jin, Zhengyu and Sun, Hao
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Subjects
More information
Scope and Contents
Contents
Objectives
To determine the diagnostic accuracy and image quality of ultra-low-dose computed tomography (ULDCT) with deep learning reconstruction (DLR) to evaluate patients with suspected urolithiasis, compared with ULDCT with hybrid iterative reconstruction (HIR) by using low-dose CT (LDCT) with HIR as the reference standard.
Methods
Pati...
Alternative Titles
Full title
Value of deep learning reconstruction at ultra-low-dose CT for evaluation of urolithiasis
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2645858488
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2645858488
Other Identifiers
ISSN
1432-1084,0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-022-08739-x
