Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimi...
Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making
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
Objectives
To evaluate a deep convolutional neural network (dCNN) for detection, highlighting, and classification of ultrasound (US) breast lesions mimicking human decision-making according to the Breast Imaging Reporting and Data System (BI-RADS).
Methods and materials
One thousand nineteen breast ultrasound images from 582 patients (age...
Alternative Titles
Full title
Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2199611733
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2199611733
Other Identifiers
ISSN
0938-7994
E-ISSN
1432-1084
DOI
10.1007/s00330-019-06118-7
