Dual-camera spectrometer with balanced detection for enhanced retinal OCT imaging in the living mouse eye
Bibliographic record
Abstract
We developed a spectral-domain optical coherence tomography (OCT) system featuring a custom dual-camera spectrometer (DCS) for balanced detection (BD) to enhance the signal-to-noise ratio in imaging. Compared to traditional single detection, the BD approach with the calibrated DCS achieves a 15.35 dB reduction in noise floor when using a supercontinuum laser. The axial resolution of the system reaches 2.9/2.2 μm in air/tissue, with a 6-dB sensitivity roll-off depth of ∼1.36 mm. In in vivo mouse retinal imaging, DCS-BD-OCT combined with temporal speckle-averaging technique can visualize highly transparent retinal ganglion cells. Additionally, for optoretinography (ORG) measurements through intensity-based approach, it successfully restored the signal dynamics obscured by noise, improving the accuracy of extracting retinal functional responses to light stimuli.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".