Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning–based comput...
Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning–based computer-assisted detection
About this item
Full title
Author / Creator
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
Purpose
To elucidate the effect of deep learning–based computer-assisted detection (CAD) on the performance of different-level physicians in detecting intracranial haemorrhage using CT.
Methods
A total of 40 head CT datasets (normal, 16; haemorrhagic, 24) were evaluated by 15 physicians (5 board-certificated radiologists, 5 radiology resid...
Alternative Titles
Full title
Improvement of the diagnostic accuracy for intracranial haemorrhage using deep learning–based computer-assisted detection
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_2449180179
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2449180179
Other Identifiers
ISSN
0028-3940
E-ISSN
1432-1920
DOI
10.1007/s00234-020-02566-x
