Optical imaging of structures within highly scattering material using an incoherent beam and a spatial filter
Bibliographic record
Abstract
Angular Domain Imaging (ADI) is a high resolution, ballistic imaging method that utilizes the angular spectrum of photons to filter multiply-scattered photons which have a wide distribution of angles from ballistic and quasi-ballistic photons which exit a scattering medium with a small distribution of angles around their original trajectory. An advantage of the ADI method is that it is suitable with a wide variety of light sources, as it is not sensitive to coherence or wavelength and does not require a pulsed source or a highly collimated beam. We extend the ADI method to transmissive imaging of scattering media using incoherent, collimated sources with a spatial filter comprised of a converging lens (focal distance of 50 to 100 mm) and pinhole aperture (diameter of 100 to 500 μm) giving acceptances angles of 0.06 to 0.6° to produce wide-beam, full-field images of planar, high contrast, phantom test objects through 5 cm thick scattering media at optical depths of up to 14.6 (scattered to ballistic photon ratio ≈ 2×106). Experimental images, obtained using a 12 mm diameter beam produced by a quartz-halogen incandescent source (beam divergence angle 0.52°, beam power < 10 mW), demonstrate the advantages of this combination of broadband, incoherent source and spatial filter: lack of interference artifacts seen with laser sources, ease of changing image magnification, simple correlation between system geometry and resolution, and ease of spectral filtration to obtain multispectral images. Monte Carlo simulation with angular tracking is used to validate the experimental results and determine system tradeoffs.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".