Efficiency of a computer-aided diagnosis (CAD) system with deep learning in detection of pulmonary n...
Efficiency of a computer-aided diagnosis (CAD) system with deep learning in detection of pulmonary nodules on 1-mm-thick images of computed tomography
About this item
Full title
Author / Creator
Publisher
Tokyo: Springer Japan
Journal title
Language
English
Formats
Publication information
Publisher
Tokyo: Springer Japan
Subjects
More information
Scope and Contents
Contents
Purpose
To evaluate the performance of a deep learning-based computer-aided diagnosis (CAD) system at detecting pulmonary nodules on CT by comparing radiologists’ readings with and without CAD.
Materials and methods
A total of 120 chest CT images were randomly selected from patients with suspected lung cancer. The gold standard of nodules...
Alternative Titles
Full title
Efficiency of a computer-aided diagnosis (CAD) system with deep learning in detection of pulmonary nodules on 1-mm-thick images of computed tomography
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2418124457
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2418124457
Other Identifiers
ISSN
1867-1071
E-ISSN
1867-108X
DOI
10.1007/s11604-020-01009-0
