Lifetime-weighted photoacoustic imaging
Bibliographic record
Abstract
Photoacoustic (PA) imaging has been utilized to quantify the lifetime profile of exogenous agents using a series of pump-probe pulses with a varying time delay; however, current techniques typically lead to long acquisition times which are sensitive to motion and cause absorption or photobleaching. We introduce a technique called lifetime-weighted imaging, which uses only three laser pulses to preferentially weight signals from chromophores with long lifetimes (including exogenous contrast agents with triplet excited states such as methylene blue and porphyrins) while nulling chromophores with short picosecond- to nanosecond-scale lifetimes (including hemoglobin). This technique detects the PA signal from a probe pulse either with or without a pump pulse. By subtracting the probe-only signal from the pump-present probe signal, we effectively eliminate signals from chromophores with short lifetimes while preserving PA signals from chromophores with long-lifetimes. We demonstrate the oxygen-dependent lifetime of both methylene blue and porphyrin-lipids and demonstrate both ground-state recovery and excited-state lifetime-weighted imaging. Lifetime-weighted PA imaging may have applications in many molecular imaging application including: photodynamic therapy dosimetry guidance and oxygen sensing.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".