Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT fo...
Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD
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Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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Background: The development and testing of a deep learning (DL)-based approach for detection and measurement of regions of Ellipsoid Zone (EZ) At-Risk to study progression in nonexudative age-related macular degeneration (AMD). Methods: Used in DL model training and testing were 341 subjects with nonexudative AMD with or without geographic atrophy...
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Automated Identification and Segmentation of Ellipsoid Zone At-Risk Using Deep Learning on SD-OCT for Predicting Progression in Dry AMD
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TN_cdi_doaj_primary_oai_doaj_org_article_9400c4ba42384787a20c3a1550b3fd1a
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9400c4ba42384787a20c3a1550b3fd1a
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ISSN
2075-4418
E-ISSN
2075-4418
DOI
10.3390/diagnostics13061178
