Multipath artifacts enable angular contrast in multimodal endoscopic optical coherence tomography
Bibliographic record
Abstract
Multipath artifacts are inherent to double-clad fiber based optical coherence tomography (OCT), appearing as ghost images blurred in the A-line direction. They result from the excitation of higher-order inner-cladding modes in the OCT sample arm which cross-couple into the fundamental mode at discontinuities and thus are detected in single-mode fiber-based interferometers. Historically, multipath artifacts have been regarded as a drawback in single fiber endoscopic multimodal OCT systems as they degrade OCT quality. In this work, we reveal that multipath artifacts can be projected into high-quality two-dimensional en face images which encode high angle backscattering features. Using a combination of experiment and simulation, we characterize the coupling of Mie-range scatterers into the fundamental image (LP 01 mode) and higher-order image (multipath artifact). This is validated experimentally through imaging of microspheres with an endoscopic multimodal OCT system. The angular dependence of the fundamental image and higher order image generated by the multipath artifact lays the basis for multipath contrast, a ratiometric measurement of differential coupling which provides information regarding the angular diversity of a sample. Multipath contrast images can be generated from OCT data where multipath artifacts are present, meaning that a wealth of clinical data can be retrospectively examined.
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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 | 0.001 |
| 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".