ArticleBiomedical optics express2017
Automated drusen detection in dry age-related macular degeneration by multiple-depth,
Article in Biomedical optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Automated detection of age-related macular degeneration in color fundus photography: a systematic review.Survey of ophthalmologyPooled it
- Drusen volume and reticular pseudodrusen volume from optical coherence tomography with deep learning as risk factors for progression to late age-related macular degeneration in eyes with reticular pseudodrusen and contralateral macular neovascularisation.The British journal of ophthalmology · 2026Article
- AI-aided segmentation of four types of drusen in volumetric OCT.Biomedical optics express · 2025Article
- High-Resolution, Motion-Corrected, Volume-Fused OCT for Investigating Longitudinal Changes in Subretinal Drusenoid Deposits in Intermediate AMD.Translational vision science & technology · 2025Article
- Deep ensemble learning for automated non-advanced AMD classification using optimized retinal layer segmentation and SD-OCT scans.Computers in biology and medicine · 2023Article
- Volume-based, layer-independent, disease-agnostic detection of abnormal retinal reflectivity, nonperfusion, and neovascularization using structural and angiographic OCT.Biomedical optics express · 2022Article
- Geographic Atrophy Progression Is Associated With Choriocapillaris Flow Deficits Measured With Optical Coherence Tomographic Angiography.Investigative ophthalmology & visual science · 2021Article
- Smartphone-based diabetic macula edema screening with an offline artificial intelligence.Journal of the Chinese Medical Association : JCMA · 2020Article
- Real-time retinal layer segmentation of OCT volumes with GPU accelerated inferencing using a compressed, low-latency neural network.Biomedical optics express · 2020Article
- Multimodal Retinal Image Analysis via Deep Learning for the Diagnosis of Intermediate Dry Age-Related Macular Degeneration: A Feasibility Study.Journal of ophthalmology · 2020Article
- Detecting and measuring areas of choriocapillaris low perfusion in intermediate, non-neovascular age-related macular degeneration.Neurophotonics · 2019Article
- Drusen diagnosis comparison between hyper-spectral and color retinal images.Biomedical optics express · 2019Article
- Artificial intelligence-based decision-making for age-related macular degeneration.Theranostics · 2019Article
- Deep learning for the segmentation of preserved photoreceptors onBiomedical optics express · 2018Article
- Automated detection of photoreceptor disruption in mild diabetic retinopathy on volumetric optical coherence tomography.Biomedical optics express · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 2 countries.
Funding
Abstract
We introduce a method to automatically detect drusen in dry age-related macular degeneration (AMD) from optical coherence tomography with minimum need for layer segmentation. The method is based on the
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.