Angular domain optical imaging of turbid media using enhanced micro-tunnel filter arrays
Bibliographic record
Abstract
We experimentally characterized the angular distribution and proportion of minimally deviated quasi-ballistic (snake) photons versus multiply scattered photons in a homogenous turbid medium. The study examined the angular distribution of photons propagating through and exiting the highly scattering medium over a narrow range about the axis of a collimated light source in trans-illumination mode. The measurements were made using an angular domain imaging system that employed one of five silicon micro-machined arrays of micro-tunnels each with a range of different acceptance angles and micro-tunnel structures. The balance between quasi-ballistic photons and unwanted multiply scattered photons accepted by the micro-machined angular filters was measured in order to determine the optimum range of acceptance angles for the system. The experiments were performed in tissue mimicking phantoms using a 2-cm thick optical cell with 0.25% Intralipid™ and a near infrared laser. This paper also presents experimental results of the angular domain imaging system employing novel micro-tunnel arrays with minimal internal reflection which can accept the non-scattered light exiting from the turbid medium within its small acceptance angle more efficiently. Our experiments reveal that image contrast was improved from 20% to 30% by employing an angular filter array with minimal internal reflection compared to conventional square-shaped filter arrays of identical size.
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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".