ArticleBiomedical optics express2025
Improving dOCT image quality with short sequences and automated binning.
Article in Biomedical optics express, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Imaging of Tissue and Cell Dynamics: introduction to the feature issue.Biomedical optics express · 2026Article
- Guide to dynamic OCT data analysis.Biomedical optics express · 2025Article
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
Dynamic optical coherence tomography (dOCT) uses signal fluctuations to contrast different cells and tissues. In this paper, we demonstrate that shortening the time base over which the signal fluctuations are evaluated reduces noise induced by motion while still maintaining a decent image quality. Automatic clustering using the neural-gas algorithm is introduced to optimize the border between the color channels. The performance of the automatic border optimization is demonstrated with 15 different tissue samples by quantitative assessment of motion-induced noise and image quality using the mean squared error (MSE) between images and the image quality parameters peak signal to noise ratio (PSNR) and structural similarity (SSIM).
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.