Coaxial cavity injected OCT and fiber laser ablation system for real-time monitoring of ablative processes part 2: toward all fiber design and dispersion control (Conference Presentation)
Bibliographic record
Abstract
Inline optical coherence tomography (OCT) has proven to be an ideal feedback mechanism for real-time depth control of high-power ablation lasers. This has found use in industrial laser ablation applications, but it has the potential to truly change the use of laser ablation in medicine. Previously, we have presented a novel design that is able to place the OCT beam ( λc = 1310nm) coaxially with the beam of a high-powered fiber laser (λ = 1064nm, Pavg=10W, Ppeak = 1kW) without the need of a dichroic mirror on the output stage. This design successfully demonstrated real-time ablation depth feedback. Development of this design was continued and further refinements have been made to improve performance and form factor, with the ultimate goal being to create a compact, low-cost, high-precision laser scalpel to be used for various surgical osteotomies. We present an improved design that, unlike before, removes the need for bulk optics in the entire system other than a single collimator and doublet lens on the output. Strategies for dispersion mismatch compensation will be discussed to optimize resolution of OCT feedback. Initial results for depth-controlled ablation of tissue is presented.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".