Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LI...
Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review
About this item
Full title
Author / Creator
Publisher
Switzerland: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Switzerland: MDPI AG
Subjects
More information
Scope and Contents
Contents
The aim of this study was to provide an overview of the literature available on machine learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection (LIDC-IDRI) database as a tool for the optimization of detecting lung nodules in thoracic CT scans. This systematic review was compiled according to Preferred Reporting Items...
Alternative Titles
Full title
Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_6d3ddb80cdea42098b503f07ae5bff5e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_6d3ddb80cdea42098b503f07ae5bff5e
Other Identifiers
ISSN
2075-4418
E-ISSN
2075-4418
DOI
10.3390/diagnostics9010029
