MétaCan
Menu
Back to cohort
Record W4319596197 · doi:10.1063/5.0132123

Single-shot wide-field imaging in reflection by using a single multimode fiber

2023· article· en· W4319596197 on OpenAlex
Yifan Liu, Panpan Yu, Yijing Wu, Ziqiang Wang, Yinmei Li, Jinyang Liang, Puxiang Lai, Lei Gong

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Physics Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Science Foundation of Anhui ProvinceChina Postdoctoral Science FoundationUniversity of Science and Technology of ChinaNational Natural Science Foundation of China
KeywordsMulti-mode optical fiberOpticsSingle shotReflection (computer programming)Frame rateSingle-mode optical fiberDigital micromirror deviceField of viewOptical fiberFiberComputer scienceMaterials sciencePhysics

Abstract

fetched live from OpenAlex

A single multimode fiber (MMF) provides almost an ideal optical channel to constitute a hair-thin endoscope for minimally invasive biomedical imaging at depths in tissue, especially if the imaging operation can be performed with one single shot in reflection mode, which, however, remains challenging to date. In this work, we present single-shot wide-field reflectance imaging by using a single MMF as the illumination unit and imaging probe simultaneously. To achieve single-shot image capture, a reflection matrix of the fiber was built by a learning-assisted approach for the universal inverse conversion from the output amplitudes to the input amplitudes. The performance was tested by imaging more than 30 000 natural scenes projected by a digital micromirror device, and an averaged Pearson correlation coefficient over 0.84 with respect to the ground truth was achieved in the experiment. Furthermore, the ability to image dynamic scenes at a high frame rate of up to 180 frames per second was demonstrated together with real-time observation of a freely moving microneedle located at the distal end of the MMF. The proposed reflection-mode single-fiber imaging scheme paves the way for practical video-rate microendoscopy at depths in tissue in a minimally invasive manner.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.955

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.030
GPT teacher head0.255
Teacher spread0.225 · 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