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Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimiza...

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimiza...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a53f11f86ace471a874b58a28072adad

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization

About this item

Full title

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization

Publisher

Switzerland: MDPI AG

Journal title

Sensors (Basel, Switzerland), 2023-07, Vol.23 (15), p.6706

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Optical coherence tomography (OCT) is widely used to detect and classify retinal diseases. However, OCT-image-based manual detection by ophthalmologists is prone to errors and subjectivity. Thus, various automation methods have been proposed; however, improvements in detection accuracy are required. Particularly, automated techniques using deep lea...

Alternative Titles

Full title

Optical Coherence Tomography Image Classification Using Hybrid Deep Learning and Ant Colony Optimization

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_a53f11f86ace471a874b58a28072adad

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_a53f11f86ace471a874b58a28072adad

Other Identifiers

ISSN

1424-8220

E-ISSN

1424-8220

DOI

10.3390/s23156706

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