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Record W4414948253 · doi:10.1364/oe.574639

3D-scanning and miniature MPM objective with improved resolution at depth scanning

2025· article· en· W4414948253 on OpenAlexfundno aff
Christoph Brandt, Wentao Wu, Qihao Liu, Shuo Tang

Bibliographic record

VenueOptics Express · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced Surface Polishing Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsLens (geology)Penetration depthRefractive indexGradient-index opticsCurvatureResolution (logic)Depth of focus (tectonics)Image resolutionFocal length

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.229
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.235
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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