Multifocus optical-resolution photoacoustic microscopy using stimulated Raman scattering and chromatic aberration
Bibliographic record
Abstract
In this Letter, multifocus optical-resolution photoacoustic microscopy is demonstrated using wavelength tuning and chromatic aberration for depth scanning. Discrete focal zones at several depth locations were created by refocusing light from a polarization-maintaining single-mode fiber pumped by a nanosecond fiber laser. The fiber and laser parameters were chosen to take advantage of stimulated Raman scattering (SRS) in the fiber to create a multiwavelength output that could then be bandpass filtered. The collimator lens and objective lens are chosen to take advantage of chromatic aberration in which each generated SRS wavelength peak focuses at a slightly different depth. The maximum amplitude of photoacoustic signals is mapped to form C-scan images. Additionally, all wavelength peaks fired simultaneously offers improved depth-of-field structural imaging at the cost of slight degradation of mainlobe-to-sidelobe ratios. Wavelength-tuned depth scanning over more than 440 μm is demonstrated, significantly greater than the ~100 μm depth of field predicted from our focused Gaussian beams. The improved depth of focus could be valuable for structural imaging of microvascular morphology without the need for mechanical scanning in the depth direction.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 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".