High repetition rate passively Q-switched fiber and microchip lasers for optical resolution photoacoustic imaging
Bibliographic record
Abstract
Optical-resolution photoacoustic microscopy is a novel imaging technology for visualizing optically-absorbing superficial structures in vivo with lateral spatial resolution determined by optical focusing rather than acoustic detection. Since scanning of the illumination spot is required, the imaging speed is limited by the scanning speed and the laser pulse repetition rate. Unfortunately, lasers with high-repetition rate and suitable pulse durations and energies are difficult to find. We are developing compact laser sources for this application. Passively Q-switched fiber and microchip lasers with pulse repetition rates up to 300 kHz are demonstrated. Using a diode-pumped microchip laser fiber-coupled to a large mode-area Yb-doped fiber amplifier we obtained 60μJ 1-ns pulses at the frequency-doubled 532-nm wavelength. The pulse-repetition rate was determined by the power of the microchip laser pump source at 808nm and may exceed 10 kHz. Additionally, a passively Q-switched fiber laser utilizing a Yb-doped double-cladding fiber and an external saturable absorber has shown to produce 250ns pulses at repetition rates of 100-300 KHz. A photoacoustic probe enabling flexible scanning of the focused output of these lasers consisted of a 45-degree glass prism in an optical index-matching fluid. Photoacoustic signals exiting the sample are deflected by the prism to an ultrasound transducer. Phantom studies with a 7.5-micron carbon fiber demonstrate the ability to image with optical rather than acoustic resolution. We believe that the high pulse-repetition rates and the potentially compact and fiber-coupled nature of these lasers will prove important for clinical imaging applications where realtime imaging performance is essential.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".