IMAGING THE RETINA BY EN FACE OPTICAL COHERENCE TOMOGRAPHY
Bibliographic record
Abstract
PURPOSE: To present the possibilities of a new system that combines optical coherence tomography (OCT) and confocal ophthalmoscopy, producing en face OCT images in patients with retinal diseases. METHODS: A prototype OCT Ophthalmoscope (OTI, Toronto, Canada) was used to scan patients with retinal conditions. The system uses a super luminescent diode (lambda = 820 nm; Deltalambda = 20 nm) and currently scans at a rate of 2 frames per second. In each frame, the OCT Ophthalmoscope simultaneously produces a transversal OCT scan and a confocal image in the X/Y plane. Both images correspond pixel to pixel. RESULTS: Between January 2002 and August 2003, >800 patients with various retinal diseases were scanned with the OCT Ophthalmoscope. Illustrative cases with regularly seen macular diseases are presented, such as macular hole and central serous retinopathy. CONCLUSION: Current difficulties as well as future possibilities of this new en face OCT ophthalmoscope are discussed. By presenting normal and pathologic transversal OCT images made by a prototype OCT Ophthalmoscope, we show that it can provide information not available using conventional OCT imaging.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".