Imaging vitreomacular interface abnormalities in the coronal plane by simultaneous combined scanning laser and optical coherence tomography
Bibliographic record
Abstract
AIM: To describe vitreoretinal imaging of eyes with vitreomacular abnormalities using high-resolution coronal-plane optical coherence tomography (OCT) scanning combined with simultaneous scanning laser ophthalmoscope (SLO) imaging. METHODS: A SLO-OCT (OTI, Canada) was used to scan 835 eyes in 736 patients with vitreomacular interface abnormalities including epiretinal membranes, macular hole, incomplete posterior vitreous detachment, vitreomacular traction syndromes and diabetic and cystoid macular oedema in a retrospective study. The longitudinal-B scan images and the transverse -C scan images in the coronal plane were used to describe vitreomacular interface abnormalities. The SLO-OCT simultaneously produces a confocal image of the retina. RESULTS: The longitudinal "B" scan and en-face "C" scan images allowed identification of tractive forces of epiretinal membrane, contour of the hyaloid membrane and changes in inner retinal surface. A simultaneously obtained OCT scan and SLO image of the fundus offered exact co-localisation of retinal structures and vitreomacular interface abnormalities. CONCLUSION: Scanning the vitreomacular interface by using combined OCT and SLO enables the visualisation and better understanding of various vitreomacular interface abnormalities, due to the ability to colocalise pathology on OCT with retinal vascular landmarks and the ability to visualise pathology from a new perspective, coronal plane parallel to retinal surface.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".