ArticleTranslational vision science & technology2017
An Automated Reference Frame Selection (ARFS) Algorithm for Cone Imaging with Adaptive Optics Scanning Light Ophthalmoscopy.
Article in Translational vision science & technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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Who cites it
62 citing papers in PubMed, 74 citations in OpenAlex.
- Use of a Retinal Phantom to Facilitate Adaptive Optics Scanning Light Ophthalmoscopy Imaging in a Multicenter Clinical Trial.Translational vision science & technology · 2026Trial
- 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
- Assessing the Relationship between Foveal Cone Density, Outer Nuclear Layer Thickness and Foveal Morphology.Ophthalmology science · 2026Article
- Article
- The Application of Supervised Machine Learning Algorithms for Image Alignment in Multi-Channel Imaging Systems.Sensors (Basel, Switzerland) · 2025Article
- Noninvasive Assessment of Ocular Structure in the Elderly 13-Lined Ground Squirrel.Advances in experimental medicine and biology · 2025Article
- Seasonal Variation in ATP-Induced Retinal Damage in the Cone-Dominant 13-Lined Ground Squirrel.Translational vision science & technology · 2024Article
- Improved tracking of corneal immune cell dynamics usingBiomedical optics express · 2024Article
- Current Status of Clinical Trials Design and Outcomes in Retinal Gene Therapy.Cold Spring Harbor perspectives in medicine · 2024Review
- Normalized weighted cross correlation for multi-channel image registration.Optics continuum · 2024Article
- Chemically induced cone degeneration in the 13-lined ground squirrel.Visual neuroscience · 2024Article
- Quantifying image quality in AOSLO images of photoreceptors.Biomedical optics express · 2024Article
- In Vivo Assessment of Retinal Phenotypes in Axenfeld-Rieger Syndrome.Investigative ophthalmology & visual science · 2024Article
- Adaptive Optics Retinal Imaging in RDH12-Associated Early Onset Severe Retinal Dystrophy.Investigative ophthalmology & visual science · 2024Article
- Peak Cone Density Predicted from Outer Segment Length Measured on Optical Coherence Tomography.Current eye research · 2024Article
- The effect of sampling window size on topographical maps of foveal cone density.Frontiers in ophthalmology · 2024Article
- Minimum intensity projection of embossed quadrant-detection images for improved photoreceptor mosaic visualisation.Frontiers in ophthalmology · 2024Article
- Pearls and Pitfalls of Adaptive Optics Ophthalmoscopy in Inherited Retinal Diseases.Diagnostics (Basel, Switzerland) · 2023Review
- Adaptive Optics Imaging of Inherited Retinal Disease.Cold Spring Harbor perspectives in medicine · 2023Review
2 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
purposeTo develop an automated reference frame selection (ARFS) algorithm to replace the subjective approach of manually selecting reference frames for processing adaptive optics scanning light ophthalmoscope (AOSLO) videos of cone photoreceptors.
methodsRelative distortion was measured within individual frames before conducting image-based motion tracking and sorting of frames into distinct spatial clusters. AOSLO images from nine healthy subjects were processed using ARFS and human-derived reference frames, then aligned to undistorted AO-flood images by nonlinear registration and the registration transformations were compared. The frequency at which humans selected reference frames that were rejected by ARFS was calculated in 35 datasets from healthy subjects, and subjects with achromatopsia, albinism, or retinitis pigmentosa. The level of distortion in this set of human-derived reference frames was assessed.
resultsThe average transformation vector magnitude required for registration of AOSLO images to AO-flood images was significantly reduced from 3.33 ± 1.61 pixels when using manual reference frame selection to 2.75 ± 1.60 pixels (mean ± SD) when using ARFS (
conclusionARFS outperforms expert observers in selecting minimally distorted reference frames in AOSLO image sequences. The low success rate in human frame choice illustrates the difficulty in subjectively assessing image distortion. TRANSLATIONAL RELEVANCE: Manual reference frame selection represented a significant barrier to a fully automated image-processing pipeline (including montaging, cone identification, and metric extraction). The approach presented here will aid in the clinical translation of AOSLO imaging.
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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.