ArticleInvestigative ophthalmology & visual science2016
Evaluating Descriptive Metrics of the Human Cone Mosaic.
Article in Investigative ophthalmology & visual science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers.
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Who cites it
109 citing papers in PubMed.
- Local Progression Kinetics of Geographic Atrophy Depends Upon the Border Location.Investigative ophthalmology & visual science · 2021Trial
- The relationship between foveal anatomy and retinal function in oculocutaneous albinism.Documenta ophthalmologica. Advances in ophthalmology · 2026Article
- In vivo adaptive optics retinal imaging reveals rod-mediated cone photoreceptor disorganization in RHO-associated retinitis pigmentosa.npj biomedical innovations · 2026Article
- Association Between PS-OCT Derived Polarimetric Entropy and RPE Cellular Metrics Measured With Adaptive Optics Imaging in Retinitis Pigmentosa.Investigative ophthalmology & visual science · 2026Article
- In Vivo Human Cone Photoreceptor Inner Segment Diameter Database Using Adaptive Optics Retinal Imaging.Investigative ophthalmology & visual science · 2026Article
- Open-Source Software Suite for Cell Detection and Segmentation in Adaptive Optics Retinal Imaging.Translational vision science & technology · 2026Article
- Cellular-Level Characterization of Cone Photoreceptors and Retinal Pigment Epithelium in Stargardt Disease with Adaptive Optics Imaging.Ophthalmology science · 2026Article
- Cone Contrast and Entropy of Adaptive Optics Images in Choroideremia.Current eye research · 2026Article
- Optoretinography in R9AP-bradyopsia reveals the essential role of G-protein signaling in the human cone elongation response.bioRxiv : the preprint server for biology · 2026Article
- Validation of a Rule-Based Automated Method for RPE Cell Detection Using Adaptive Optics Transscleral Flood Illumination.Translational vision science & technology · 2026Article
- ƒ(Cell): Software for Reproducible Analysis of Optoretinograms.Translational vision science & technology · 2026Article
- Selected Aspects of Optical Coherence Tomography and Adaptive Optics in Patients with Increased Body Mass Index.Biomedicines · 2026Article
- Non-uniform signal pooling across the foveola.Current biology : CB · 2025Article
- Asymmetries in Foveal Vision.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- In Vivo Cone Photoreceptor Topography of the Human Foveola.Investigative ophthalmology & visual science · 2025Article
- The Cone Optoretinogram as a Function of Retinal Eccentricity.Photonics · 2025Article
- The USH3A causative gene clarin1 functions in Müller glia to maintain retinal photoreceptors.PLoS genetics · 2025Article
- Noninvasive Assessment of Ocular Structure in the Elderly 13-Lined Ground Squirrel.Advances in experimental medicine and biology · 2025Article
- Asymmetries in foveal vision.bioRxiv : the preprint server for biology · 2024Article
- Changes in Waveguiding Cone Photoreceptors and Color Vision in Patients With Diabetes Mellitus.Investigative ophthalmology & visual science · 2024Article
49 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
Abstract
purposeTo evaluate how metrics used to describe the cone mosaic change in response to simulated photoreceptor undersampling (i.e., cell loss or misidentification).
methodsUsing an adaptive optics ophthalmoscope, we acquired images of the cone mosaic from the center of fixation to 10° along the temporal, superior, inferior, and nasal meridians in 20 healthy subjects. Regions of interest (n = 1780) were extracted at regular intervals along each meridian. Cone mosaic geometry was assessed using a variety of metrics - density, density recovery profile distance (DRPD), nearest neighbor distance (NND), intercell distance (ICD), farthest neighbor distance (FND), percentage of six-sided Voronoi cells, nearest neighbor regularity (NNR), number of neighbors regularity (NoNR), and Voronoi cell area regularity (VCAR). The "performance" of each metric was evaluated by determining the level of simulated loss necessary to obtain 80% statistical power.
resultsOf the metrics assessed, NND and DRPD were the least sensitive to undersampling, classifying mosaics that lost 50% of their coordinates as indistinguishable from normal. The NoNR was the most sensitive, detecting a significant deviation from normal with only a 10% cell loss.
conclusionsThe robustness of cone spacing metrics makes them unsuitable for reliably detecting small deviations from normal or for tracking small changes in the mosaic over time. In contrast, regularity metrics are more sensitive to diffuse loss and, therefore, better suited for detecting such changes, provided the fraction of misidentified cells is minimal. Combining metrics with a variety of sensitivities may provide a more complete picture of the integrity of the photoreceptor mosaic.
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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.