Laser tissue coagulation and concurrent optical coherence tomography through a double-clad fiber coupler
Bibliographic record
Abstract
Double-clad fiber (DCF) is herein used in conjunction with a double-clad fiber coupler (DCFC) to enable simultaneous and co-registered optical coherence tomography (OCT) and laser tissue coagulation. The DCF allows a single channel fiber-optic probe to be shared: i.e. the core propagating the OCT signal while the inner cladding delivers the coagulation laser light. We herein present a novel DCFC designed and built to combine both signals within a DCF (>90% of single-mode transmission; >65% multimode coupling). Potential OCT imaging degradation mechanisms are also investigated and solutions to mitigate them are presented. The combined DCFC-based system was used to induce coagulation of an ex vivo swine esophagus allowing a real-time assessment of thermal dynamic processes. We therefore demonstrate a DCFC-based system combining OCT imaging with laser coagulation through a single fiber, thus enabling both modalities to be performed simultaneously and in a co-registered manner. Such a system enables endoscopic image-guided laser marking of superficial epithelial tissues or laser thermal therapy of epithelial lesions in pathologies such as Barrett's esophagus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".