Photoacoustic tomography as a method to estimate the optical fluence distribution in turbid media
Bibliographic record
Abstract
Currently, there are no non-invasive experimental methods available for measuring optical fluence distributions in tissue. We present photoacoustic tomography (PAT) as a method to approximate the relative optical fluence distribution in a homogeneous optically scattering medium. Three-dimensional photoacoustic images were captured with a near-full view PAT scanner in phantoms with known optical absorption and scatter properties. Resultant 3D PAT images were compared to the expected optical fluence distributions from Monte Carlo simulations and diffusion theory using volumetric and shape analysis. Volumetric analysis of PAT images compared well with the optical fluence distributions from simulation. Dice similarity coefficients ranged from 51 to 82%. The reduced scattering coefficient estimated from PAT images compared well to estimates from simulations for values below 0.5 mm -1 . Near full-view PAT has been found to be useful for estimating the optical fluence distribution in an optically scattering medium. Further development is needed to extend the measurement range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".