ArticleTranslational vision science & technology2025
Evaluation of Deep Learning-Based OCTA Denoising in Retinal Vessel Assessment.
Article in Translational vision science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
1 citing paper in PubMed.
- Association of Serum Meteorin-Like with OCTA Metrics in Type 2 Diabetic Nonproliferative Retinopathy: A Cross-Sectional Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate the performance of the N2V2 denoising algorithm on optical coherence tomography angiography (OCTA) retinal vasculature quantification. Methods: OCTA scans (3 × 3, 6 × 6, and 21 × 21 mm) were acquired from patients with diabetes using Topcon Triton before/after denoising. Perceived image quality was assessed by three ophthalmologists on a 5-point scale (capillary details in the superficial capillary plexus [SCP] and deep capillary plexus [DCP] of 3 × 3 and 6 × 6 mm scans, and vessel continuity and nonperfusion boundaries in 21 × 21 mm scans), and by objective metrics including contrast-to-noise ratio, peak signal-to-noise ratio, edge preservation index, and structural similarity index measurement. Diagnostic interpretability was evaluated through annotation of microaneurysm and vascular beading counts, foveal avascular zone margins, and peripheral nonperfusion borders. Quantitative reproducibility was assessed for vessel density, foveal avascular zone metrics (area, perimeter, circularity), and peripheral nonperfusion area delineations. Results: We included 145 eyes (mean patient age, 63.97 ± 9.25 years; 40.26% female) (35.17% no diabetic retinopathy, 33.10% nonproliferative diabetic retinopathy, and 31.72% proliferative diabetic retinopathy). Subjective vessel visualization improved in 3 × 3 (ΔSCP, 1.66 ± 0.39; ΔDCP, 1.90 ± 0.43), 6 × 6 (ΔSCP, 1.68 ± 0.36; ΔDCP, 2.11 ± 0.33), and 21 × 21 mm scans (Δvessels, 1.79 ± 0.37; Δnonperfusion, 1.61 ± 0.38) (all P < 0.001). Denoising objectively increased the contrast-to-noise ratio from poor (1.33-1.68) to moderate (2.90-3.97) (P < 0.001), and the peak signal-to-noise ratio (16.74-18.53 dB), structural similarity index measurement (0.60-0.72), and edge preservation index (0.71-0.79) reached moderate levels. Diagnostic interpretability showed most microaneurysms (64.17% SCP, 87.32% DCP) and venous beading (98.76%) remaining detectable. Vessel density decreased in 3 × 3 mm (ΔSCP, -5.81%; ΔDCP, -4.18%) and 6 × 6 mm scans (ΔSCP, -11.89%; ΔDCP, -5.23%; P < 0.001). The foveal avascular zone area increased slightly (Δ+0.01 mm²; P = 0.02), the perimeter expanded (Δ+0.53 mm; P < 0.001), and circularity decreased (Δ-0.16; P < 0.001), with similar peripheral nonperfusion area (Δ+4.84 mm²; P = 0.49). Conclusions: N2V2 enhances OCTA quality and visualization, which may support more accurate retinal change assessments. Translational Relevance: The N2V2 denoising algorithm can potentially advance the routine clinical use of OCTA by improving the visualization and features quantification.
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.