Computer-Based Video Analysis of Cerebral Arterial Geometry Using the Natural Fluorescence of the Arterial Wall and Contrast Enhancement Techniques
Bibliographic record
Abstract
The walls of mammalian arteries fluoresce with ultraviolet excitation in the wavelength range of 350-400 nm. We are using this property of natural fluorescence in conjunction with episcopic fluorescence microscopy, frozen section techniques, selective contrast enhancement, and a semi-automatic computer-based video analysis system to obtain dimensional data and 3-D coordinate maps of cerebral bifurcation geometry. The computer-video analysis system, comprised of commercially available video components, a Cromemco Z2D Computer, and electronic components built in our lab has a resolution of +/- 1/256 mm at full-screen magnification. Our technique is based upon measurement of the video image of the block face during frozen sectioning of cerebral bifurcations. This technique allows us to obtain axially symmetric coordinate maps of cerebral bifurcation geometry without the use of block markers. In addition to mapping lumenal and adventitial surfaces the system can be used to map atheromatous lesions and the outline of the internal elastic lamina. Our initial geometrical data suggest a linear increase of 50-60% in cross-sectional area in the apical region and widening of the apical region in the plane of the daughter branches.
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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 | 0.001 |
| 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) | 0.003 | 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".