Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction
Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction
About this item
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Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
Formats
Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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More information
Scope and Contents
Contents
Objectives
Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists’ visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compa...
Alternative Titles
Full title
Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_swepub_primary_oai_swepub_ki_se_635267
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_swepub_primary_oai_swepub_ki_se_635267
Other Identifiers
ISSN
1432-1084,0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-023-09985-3
