ArticleBiomedical optics express2023
Deep learning-enabled volumetric cone photoreceptor segmentation in adaptive optics optical coherence tomography images of normal and diseased eyes.
Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- ISOSNet: a unified framework for cone photoreceptor detection and inner segment and outer segment length measurement from AO-OCT B-scans.Biomedical optics express · 2025Article
- 3D-printed phantoms for measuring lateral resolution and contrast performance of ophthalmic adaptive optics imaging systems.Biomedical optics express · 2025Article
- Three-dimensional C-scan-based generation adversarial network with synthetic input to improve optical coherence tomography angiography.Journal of biomedical optics · 2025Article
- Identifying retinal pigment epithelium cells in adaptive optics-optical coherence tomography images with partial annotations and superhuman accuracy.Biomedical optics express · 2024Article
- Reducing manual labeling requirements and improved retinal ganglion cell identification in 3D AO-OCT volumes using semi-supervised learning.Biomedical optics express · 2024Article
- Quantification of Human Photoreceptor-Retinal Pigment Epithelium Macular Topography with Adaptive Optics-Optical Coherence Tomography.Diagnostics (Basel, Switzerland) · 2024Article
- Semi-supervised generative adversarial learning for denoising adaptive optics retinal images.Biomedical optics express · 2024Article
- Unleashing the power of optical attenuation coefficients to facilitate segmentation strategies in OCT imaging of age-related macular degeneration: perspective.Biomedical optics express · 2023Article
- Introduction to Visual and Physiological Optics feature issue ofBiomedical optics express · 2023Article
- Deep learning-enabled volumetric cone photoreceptor segmentation in adaptive optics optical coherence tomography images of normal and diseased eyes.Biomedical optics express · 2023Article
- Automated Cone Photoreceptor Detection in Adaptive Optics Flood Illumination Ophthalmoscopy.Ophthalmology scienceArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Objective quantification of photoreceptor cell morphology, such as cell diameter and outer segment length, is crucial for early, accurate, and sensitive diagnosis and prognosis of retinal neurodegenerative diseases. Adaptive optics optical coherence tomography (AO-OCT) provides three-dimensional (3-D) visualization of photoreceptor cells in the living human eye. The current gold standard for extracting cell morphology from AO-OCT images involves the tedious process of 2-D manual marking. To automate this process and extend to 3-D analysis of the volumetric data, we propose a comprehensive deep learning framework to segment individual cone cells in AO-OCT scans. Our automated method achieved human-level performance in assessing cone photoreceptors of healthy and diseased participants captured with three different AO-OCT systems representing two different types of point scanning OCT: spectral domain and swept source.
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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.