ReticularNet: Automated Pixel-Level Segmentation of Reticular Pseudodrusen on Near-Infrared Reflectance Images by Deep Learning

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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Publication Details

Journal
Ophthalmology Science
Published
2025-12-18
DOI
https://doi.org/10.1016/j.xops.2025.101038
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

ReticularNet: Automated Pixel-Level Segmentation of Reticular Pseudodrusen on Near-Infrared Reflectance Images by Deep Learning

Ophthalmology Science
Cell Image Analysis Techniques
article

ReticularNet: Automated Pixel-Level Segmentation of Reticular Pseudodrusen on Near-Infrared Reflectance Images by Deep Learning

article en

Abstract

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Ophthalmology ScienceVol. 6(2)
Roche (Switzerland) (CH), National Institutes of Health (US), University of Wisconsin System (US), University of Wisconsin–Madison (US), National Eye Institute (US), University of Colorado Anschutz Medical Campus (US)
Openalex Percentile: Top 22%
Cell Image Analysis Techniques
DOIOpen Access PDFOpenAlex
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