Wide dynamic range detection of bidirectional flow in Doppler optical coherence tomography using a two-dimensional Kasai estimator
Bibliographic record
Abstract
We demonstrate extended axial flow velocity detection range in a time-domain Doppler optical coherence tomography (DOCT) system using a modified Kasai velocity estimator with computations in both the axial and transverse directions. For a DOCT system with an 8 kHz rapid-scanning optical delay line, bidirectional flow experiments showed a maximum detectable speed of >56 cm/s using the axial Kasai estimator without the occurrence of aliasing, while the transverse Kasai estimator preserved the approximately 7 microm/s minimum detectable velocity to slow flow. By using a combination of transverse Kasai and axial Kasai estimators, the velocity detection dynamic range was over 100 dB. Through a fiber-optic endoscopic catheter, in vivoM-mode transesophageal imaging of the pulsatile blood flow in rat aorta was demonstrated, for what is for the first time to our knowledge, with measured peak systolic blood flow velocity of >1 m/s, while maintaining good sensitivity to detect aortic wall motion at <2 mm/s, using this 2D Kasai technique.
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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 | 0.003 |
| 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 | 0.001 |
| 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 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".