A handheld photoacoustic microscopic probe integrating a transparent ultrasound transducer and a fiber scanner
Bibliographic record
Abstract
Photoacoustic microscopy (PAM) has been widely used in biomedical studies to provide high-resolution 3D anatomical, functional, and molecular images of living subjects. While handheld PAM systems have been proposed to extend its applicability, it has proved challenging to achieve a compact device that combines fast imaging with high spatial resolution and signal to noise ratio. Here we demonstrate a handheld PAM probe integrating a fiber scanner and high-frequency transparent ultrasound transducer (TUT), called hPAM-TUT. The compact system (measuring 17 mm in diameter, with a 90 mm long rigid body) achieves high lateral and axial resolutions (7 and 47 μm, respectively), has a 2.6 mm diameter field of view, and delivers a single volumetric image in 1.5 s. In living rats, we used hPAM-TUT to visualize various abdominal organs, and in mice we used it to observe epinephrine-induced vascular changes and image the anatomy and functioning of lymphatic vessels after injection of Evans blue dye. Additionally, we successfully delineated murine vascular networks in early metastatic tumors. This handheld PAM probe shows promise for both clinical and research applications in such fields as dermatology, oncology, and intraoperative imaging.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".