F-mode ultraviolet photoacoustic remote sensing for label-free virtual H&E histopathology using a single excitation wavelength
Bibliographic record
Abstract
Photoacoustic remote sensing (PARS) is a novel all-optical imaging modality that allows for non-contact detection of initial photoacoustic pressures. Using 266-nm excitation pulses, ultraviolet PARS (UV-PARS) has previously demonstrated imaging contrast for cell nuclei in histological samples with < 400 n m resolution. In prior PARS-based imaging schemes, the signal amplitude at an interrogation point was determined by the maximum deflection from the DC scattering signal in response to a pulsed excitation. This method, however, does not take into consideration additional information encoded in the frequency domain of the recorded PARS signals. Here, we present a frequency domain technique called F-mode PARS that can be used to generate images with nuclear and cytoplasmic enhanced contrast, enabling label-free virtual hematoxylin-and-eosin-like microscopy, using only a single excitation wavelength. With F-mode processing, we have been able to demonstrate contrast-to-noise ratios of up to 38 dB between cell nuclei and surrounding cytoplasm, which represents up to a 25-dB improvement over previous implementations of UV-PARS systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".