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Record W1973781788 · doi:10.1117/1.3593148

Development of a catadioptric endoscope objective with forward and side views

2011· article· en· W1973781788 on OpenAlexafffund
Roy Chih Chung Wang, M. Jamal Deen, David Armstrong, Qiyin Fang

Bibliographic record

VenueJournal of Biomedical Optics · 2011
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaIran Telecommunication Research CenterKorea Science and Engineering FoundationNational Applied Research Laboratories
KeywordsCatadioptric systemEndoscopeOptical transfer functionOpticsAutofluorescenceComputer scienceDigital micromirror deviceEntrance pupilDesign for manufacturabilityImage qualityLens (geology)Computer visionArtificial intelligencePhysicsPupilMedicineRadiology

Abstract

fetched live from OpenAlex

Autofluorescence endoscopy is a promising functional imaging technique to improve screening of pre-cancerous or early cancer lesions in the gastrointestinal (GI) tract. Tissue autofluorescence signal is weak compared to white light reflectance imaging. Conventional forward-viewing endoscopes are inefficient in the collection of light from objects of interest along on the GI luminal wall. A key component of a complete autofluorescence endoscope is the light collection module. In this paper, we report the design, optimization, prototype development, and testing of an endoscope objective that is capable of acquiring simultaneous forward and radial views. The radial-view optical design was optimized for a balance between image quality and light collection. Modulation transfer function (MTF), entrance pupil radius, manufacturability, and field-of-view were parameters used in the lens optimization. In comparison with the typical forward-viewing endoscopes, our nonsequential ray trace simulations suggest the proposed radial-view design is more practical in the light collection. To validate the proposed simulation methods, a 3:1 scaled-up prototype was fabricated. Contrast measurements were taken with the prototype, and then compared with the simulated MTF.

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 score0.618
Threshold uncertainty score0.273

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 head0.018
GPT teacher head0.217
Teacher spread0.200 · 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

Citations25
Published2011
Admission routes2
Has abstractyes

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