Photoacoustic F-Mode imaging for scale specific contrast in biological systems
Bibliographic record
Abstract
Abstract In photoacoustic (PA) imaging, time domain reconstruction techniques are the current gold standard for image formation. While these techniques provide high-resolution spatial maps of optical absorption, they neglect the structural information encoded in the frequency domain of the broadband PA signals. In this work, we introduce a frequency domain technique for PA image formation, termed F-Mode. By leveraging information contained in the frequency content of PA signals, F-Mode can be used to generate images with scale-specific contrast. To demonstrate the robustness of our technique, we apply F-Mode to datasets acquired using both PA tomography and PA microscopy systems, utilizing linear array and single-element transducers with central frequencies ranging from 40–400 MHz. Here we show that the technique can be used to: differentiate between vessels and microspheres of different size in phantoms, enhance visualization of organelles in cultured cells, and selectively display single blood vessels in vivo in zebrafish larvae.
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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) | 0.000 | 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 | 0.000 | 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".