3D-scanning and miniature MPM objective with improved resolution at depth scanning
Bibliographic record
Abstract
Achieving 3D imaging in a compact handheld or microendoscopic MPM system requires a miniature objective and scanner. We report on a miniature objective design that can perform depth scanning and maintain good focusing performance over a wide depth scanning range. Our objective was composed of an aspheric lens and a plano-convex lens (PCX). Depth scanning was achieved by actuating the aspheric lens using a shape memory alloy actuator. The challenge of focal spot degradation during depth scanning was addressed by compensating the spherical aberration induced by refractive index mismatch with that by the curvature of the PCX. Compared with other aspheric lens-based objectives and gradient index objective, our custom objective improved the performance in focal spot degradation and penetration depth. The resolution and signal intensity remained fairly constant over ∼400 µm depth scanning range. The advantages of depth scanning and deep penetration in a miniature profile of our objective design show great potential in clinical MPM applications.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".