Development of Broadband Sources Based on Semiconductor Optical Amplifiers and Erbium-Doped Fiber Amplifiers for Optical Coherence Tomography
Bibliographic record
Abstract
Broadband sources (BBSs) are commonly used in a wide range of applications in optical communication systems and biophotonics. They are particularly useful tools for biomedical imaging techniques such as optical coherence tomography (OCT). In order to obtain high image quality, we have developed a novel, low-cost, BBS based on semiconductor optical amplifiers combined with an erbium-doped fiber amplifier. It has bandwidth (BW) between 100 and 150 nm (ranging from 1450 to 1630 nm) and output power between 4 and 9 mW. Several configurations optimizing the BW, the spectral shape, and the output power are compared and tested in a time-domain OCT system. Images and OCT autocorrelation traces are compared for each configuration. The different sources provide an axial resolution of$\approx \hbox{10}\;\mu$m, with low sidelobes in the OCT autocorrelation function. Images realized with each configuration are compared with more expensive sources and systems such as Ti:sapphire lasers and spectral domain OCT system. It is shown that the optimized sources can have a global image aspect that is comparable with these systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".