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Record W2913483180 · doi:10.1364/ol.44.000675

Truncated-correlation photothermal coherence tomography derivative imaging modality for small animal in vivo early tumor detection

2019· article· en· W2913483180 on OpenAlexafffund
Hai Zhang, Pantea Tavakolian, Koneswaran Sivagurunathan, Andreas Mandelis, Wei Shi, Fei‐Fei Liu

Bibliographic record

VenueOptics Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsOptical coherence tomographyPhotothermal therapyPreclinical imagingIn vivoContrast (vision)Medical imagingMolecular imagingOptical imagingMaterials scienceOpticsBiomedical engineeringMedicinePathologyNuclear medicineRadiologyBiologyNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Early cancer non-invasive diagnosis is a leading medical topic worldwide due to the threat to human life and the high death rate of this disease. Light-absorption-based thermophotonic diagnostic imaging is well positioned for this challenge thanks to its speed, safety, and high molecular contrast advantages. In this Letter, an enhanced truncated-correlation photothermal coherence tomography (TC-PCT) imaging modality is presented for early in vivo tumor detection and tested using a nude mouse thigh. Compared with conventional TC-PCT, the enhanced imaging modality was found to exhibit higher contrast that contributed to the precise measurement of the size and shape of the detected tumor. The experimental results were validated following histological analysis from hematoxylin and eosin staining. This increased contrast advantage gives rise to possible clinical applications in early tumor detection and treatment and in monitoring the effects of anti-tumor drugs.

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 score0.810
Threshold uncertainty score0.811

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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

Citations15
Published2019
Admission routes2
Has abstractyes

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