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Record W3048555272 · doi:10.1038/s41598-020-70815-3

Non-invasive in-vivo 3-D imaging of small animals using spatially filtered enhanced truncated-correlation photothermal coherence tomography

2020· article· en· W3048555272 on OpenAlexafffund
Pantea Tavakolian, Sohrab Roointan, Andreas Mandelis

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCalifornia HIV/AIDS Research Program
KeywordsOptical coherence tomographyPhotothermal therapyIn vivoPreclinical imagingBiomedical engineeringImage resolutionDiffusion imagingMaterials scienceBrain tumorTomographyDiffusion MRIMagnetic resonance imagingNuclear magnetic resonancePathologyOpticsMedicineRadiologyBiologyPhysics

Abstract

fetched live from OpenAlex

We present enhanced truncated-correlation phototothermal coherence tomography (eTC-PCT) for non-invasive three-dimensional imaging of small animals. Tumor detection is reported in a mouse thigh by injecting cancerous cells in the thigh followed by eTC-PCT imaging. Detection of the tumor 3 days after injection may lead to potential for using the eTC-PCT method for cancer treatment studies. eTC-PCT was also applied successfully to non-invasive in-vivo mouse brain structural imaging. A unique spatial-gradient-gate adaptive filter was introduced in a scanned mode along the (x,y) coordinates of camera images from different sub-cranial depths, revealing absorber true spatial extent from diffusive photothermal images and restoring pre-diffusion lateral image resolution beyond the Rayleigh criterion limit in diffusion-wave imaging science. The spatial resolution and contrast enhancement demonstrated in photothermal in-vivo and ex-vivo images of the mouse brain revealed not only vascular structures but also other brain structures, such as the brain hemispheres, cerebellum, and olfactory lobes.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.890

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 head0.013
GPT teacher head0.210
Teacher spread0.197 · 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

Citations9
Published2020
Admission routes2
Has abstractyes

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