Imaging dynamic processes using fiber laser optical-resolution photoacoustic microscopy
Bibliographic record
Abstract
Recently we have reported in vivo near-real-time volumetric optical-resolution photoacoustic microscopy (OR-PAM) using a high pulse-repetition-rate (PRR) nanosecond fiber-laser to realize 2 volumetric image frames per second (fps) within 1mm × 1mm field of view (FOV). Based on our previous OR-PAM system, we are developing a label-free realtime OR-PAM system in reflection mode for higher frame-rates. The system permits imaging of microcirculation hemodynamics, and helps make the technology easier to use for biologists, providing real-time feedback for focusing and positioning. Using a nanosecond-pulsed 532-nm fiber laser combined with fast-scanning mirrors, our proposed system demonstrated its capability of sustained in vivo imaging of horizontal and vertical translation at 0.5 fps for 1mm × 1mm FOV (400 × 400 pixels). Also, real-time in vivo imaging of blood flow at 30 fps for 250μm × 250μm FOV (100 × 100 pixels) was demonstrated. It is anticipated that the real-time nature of the system should prove important in clinical and preclinical adaption, and may prove useful for functional brain imaging studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".