Laser speckle size and contrast investigation of volumetric scattering from controlled turbid phantoms and mouse skin tissues
Bibliographic record
Abstract
The potential of spatial laser speckle analysis to interrogate scattering properties of volumetric optical tissue-like phantoms and biological tissues is examined. The simple and inexpensive experimental setup consists of a HeNe laser illuminating turbid samples to acquire speckle patterns in backscattering geometry. Theoretical Monte Carlo simulations of subsurface light fluence patterns and scattering statistics are used to interpret the experimental findings, in an effort to help expand established speckle theory from rough surface effects to volumetric scattering processes. Beyond controlled phantom studies, initial results from normal and pathologic biological tissues are also presented and discussed. Building on previous research that attempts to link specific stochastic speckle metrics to medium scattering properties, this study suggests that a combination of speckle contrast and speckle size can be related to varying scattering coefficients, toward distinguishing samples by their underlying scatterer size and concentration.
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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 | 0.000 | 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 | 0.000 |
| 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".