The Foveal Avascular Zone Image Database (FAZID)
Bibliographic record
Abstract
The Foveal Avascular Zone (FAZ) is of clinical importance since the vascular arrangement around the fovea changes with disease and refractive state of the eye. In order to test and validate newly developed automated segmentation algorithms, we have created a public dataset of these retinal fundus images consisting of a total of 304 different images classified into: Diabetic (107), Myopic (109) and Normal (88) eyes. The images are of dimensions 420 x 420 pixels corresponding to 6mm x 6mm dimension of the retina. For each type of image, clear and manually segmented by a clinical expert (ground truth) are available. Please use the following citation if you use the database “Jothi Balaji, J.; Agarwal, A.; Raman, R., et al., Comparison of Foveal Avascular Zone in Diabetic Retinopathy, High Myopia and Normal Fundus images. Ophthalmic Technologies XXX, Vol 11218-59. Proc. SPIE (2020).” (To be appeared)
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.024 |
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".