ArticleBiomedical optics express2023
Adaptive balanced detection spectral domain optical coherence tomography.
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 7 papers.
What it found
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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.
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Who cites it
7 citing papers in PubMed.
- Vis-OCT Explorer: an open-source software for visible-light optical coherence tomography data processing.Biomedical optics express · 2026Article
- Deep-learning-based optical coherence tomography reconstruction for high-speed and contrast morphology and vasculature imaging.Journal of biomedical optics · 2026Article
- Visible-light optical coherence tomography and its applications.Neurophotonics · 2025Review
- Visible light polarization-sensitive optical coherence tomography with balanced detection.Journal of biomedical optics · 2025Article
- Development of next generation low-cost OCT towards improved point-of-care retinal imaging.Biomedical optics express · 2025Article
- Review
- Longitudinal imaging of vitreal hyperreflective foci in mice with acute optic nerve damage using visible-light optical coherence tomography.Optics letters · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Balanced detection optical coherence tomography (BD-OCT) enables near-shot noise-limited imaging by suppressing wavelength-dependent relative intensity noise (RIN) originating from the light source. In spectral-domain BD-OCT (SD-BD-OCT), the level of RIN suppression relies on the co-registration accuracy of the spectra simultaneously captured by two independent spectrometers. However, existing matching methods require careful pre-calibration using a RIN-dominated dataset or subjective post-processing using a signal-dominated dataset. We developed an adaptive subpixel matching approach, referred to as adaptive balance, that can be applied to any SD-BD-OCT dataset regardless of RIN or signal level without the need for pre-calibration. We showed that adaptive balance performed comparable to or better than reported methods by imaging phantoms with varying spectrometer camera gain, exposure time, and supercontinuum laser repetition rate. We further demonstrated the benefits of adaptive balance in human retinal imaging.
Identifiers
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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.