Incoherent source angular domain imaging through complex three-dimensional scattering structures
Bibliographic record
Abstract
Scattering of photons in biological imaging is a known factor of degrading image resolution and quality. Angular Domain Imaging (ADI) is a technique which utilizes the angular distribution of photons to filter out multiple-scattering photons and accept only photons with small angular deviation from their original trajectories. The advantage of ADI is that it does not require a high optical quality, coherent, or pulsed source to acquire quality image. Initial experiments with Spatialfrequency Filter (SFF) ADI on simple liquid scattering test phantom showed good results as it can image through media with scattering ratio (SR) of 106:1. Previous work with complex 3D aquatic species eliminated scattering but showed optical interference patterns from the coherent laser sources. With SFF ADI, our target is to image through a complex 3D scattering structure with multilayer of different refractive indices and scattering coefficient from an Intralipid-infused polymer/agar, and a small species called Branchiostoma lanceolatum, a lancelet that is 5-8cm long and ~5mm thick. To remove interference, several narrow wavelength-band LEDs were used as illumination sources with one peaks at 630nm and the other peaks at 415nm. The LEDs are collimated and illuminates the 3D structure/lancelet in a water-filler container while a SFF removes the scattered photons before the imager. This allows us to reduce the optical interference and to study the impact of switching from coherent laser source into an incoherent narrow wavelength-band source. Hence, it allows us to investigate the enhancement of imaging the internal structures using the incoherent narrow wavelength-band source.
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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 | 0.001 |
| 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 | 0.000 | 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".