Review of speckle and phase variance optical coherence tomography to visualize microvascular networks
Why this work is in the frame
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Bibliographic record
Abstract
High-resolution mapping of microvasculature has been applied to diverse body systems, including the retinal and choroidal vasculature, cardiac vasculature, the central nervous system, and various tumor models. Many imaging techniques have been developed to address specific research questions, and each has its own merits and drawbacks. Understanding, optimization, and proper implementation of these imaging techniques can significantly improve the data obtained along the spectrum of unique research projects to obtain diagnostic clinical information. We describe the recently developed algorithms and applications of two general classes of microvascular imaging techniques: speckle-variance and phase-variance optical coherence tomography (OCT). We compare and contrast their performance with Doppler OCT and optical microangiography. In addition, we highlight ongoing work in the development of variance-based techniques to further refine the characterization of microvascular networks.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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