Detection of Blood Vessels in Fundus Images of the Retina using Gabor Wavelets
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Bibliographic record
Abstract
The monitoring of the effects of diabetes, hypertension, and premature birth on the visual system can be assisted by quantitative analysis of the vascular architecture of the retina. The application of image analysis techniques in ophthalmology becomes possible after the desired features have been detected through the use of an appropriate method. We propose image processing techniques for the detection of blood vessels in the retina. The methods include the design of a bank of directionally sensitive Gabor filters for several values of the scale and elongation parameters. Forty images of the retina from the DRIVE database were used to evaluate the performance of the methods. High efficiency in the detection of blood vessels with the area under the receiver operating characteristics curve of up to 0.96 was achieved.
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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 | 0.001 |
| 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 it