Multimodal adaptive optics retinal imager: design and performance
Bibliographic record
Abstract
Optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO) are complementary imaging modalities, the combination of which can provide clinicians with a wealth of information to detect retinal diseases, monitor disease progression, or assess new therapies. Adaptive optics (AO) is a tool that enables correction of wavefront distortions from ocular aberrations. We have developed a multimodal adaptive optics system (MAOS) for high-resolution multifunctional use in a variety of research and clinical applications. The system integrates both OCT and SLO imaging channels into an AO beam path. The optics and hardware were designed with specific features for simultaneous SLO/OCT output, for high-fidelity AO correction, for use in humans, primates, and small animals, and for efficient location and orientation of retinal regions of interest. The MAOS system was tested on human subjects and rodents. The design, performance characterization, and initial representative results from the human and animal studies are presented and discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".