A novel deep learning architecture outperforming 'off‑the‑shelf' transfer learning and feature‑based...
A novel deep learning architecture outperforming 'off‑the‑shelf' transfer learning and feature‑based methods in the automated assessment of mammographic breast density
About this item
Full title
Author / Creator
Publisher
Greece: Spandidos Publications
Journal title
Language
English
Formats
Publication information
Publisher
Greece: Spandidos Publications
Subjects
More information
Scope and Contents
Contents
Potentially suspicious breast neoplasms could be masked by high tissue density, thus increasing the probability of a false‑negative diagnosis. Furthermore, differentiating breast tissue type enables patient pre‑screening stratification and risk assessment. In this study, we propose and evaluate advanced machine learning methodologies aiming at an o...
Alternative Titles
Full title
A novel deep learning architecture outperforming 'off‑the‑shelf' transfer learning and feature‑based methods in the automated assessment of mammographic breast density
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6787954
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6787954
Other Identifiers
ISSN
1021-335X
E-ISSN
1791-2431
DOI
10.3892/or.2019.7312
