Fiber lenses for ultra-small probes used in optical coherent tomography
Bibliographic record
Abstract
We present a design, construction and characterization of different variations of GRIN and ball fiber lenses, which were recently proposed for ultra-small biomedical imaging probes. Those fiber lens modules are made of a single mode fiber and a GRIN or ball fiber lens with or without a fiber spacer between them. The lens diameters are smaller than 0.3 mm. We discuss design methods, fabrication techniques, and measuring performance of the fiber lenses. The experimental results are compared to their modeling results. The fabrication of a high quality beam director for both lens types is presented as well. These fiber integrated beam directors could be added on the tips of the fiber lenses for side-view probes. A needle probe made by these fiber lenses is demonstrated as a sample of the ultra-small probe for biomedical imaging application. In vivo human finger images acquired by a swept source optical coherence tomography using the fiber lenses with different beam profiles were shown, which indicates the important impact of fiber
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".