Log in to save to my catalogue

RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on re...

RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on re...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c941d8aad29d42f58a89fbd61fdda5ca

RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on retinal structure

About this item

Full title

RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on retinal structure

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2021-06, Vol.11 (1), p.12562-12562, Article 12562

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Glaucoma is the leading cause of irreversible blindness in the world, affecting over 70 million people. The cumbersome Standard Automated Perimetry (SAP) test is most frequently used to detect visual loss due to glaucoma. Due to the SAP test’s innate difficulty and its high test-retest variability, we propose the RetiNerveNet, a deep convolutional...

Alternative Titles

Full title

RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on retinal structure

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_c941d8aad29d42f58a89fbd61fdda5ca

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_c941d8aad29d42f58a89fbd61fdda5ca

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-021-91493-9

How to access this item