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Record W2024391068 · doi:10.1364/boe.5.001664

Hybrid FMT-MRI applied to in vivo atherosclerosis imaging

2014· article· en· W2024391068 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomedical Optics Express · 2014
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsPolytechnique MontréalMontreal Heart Institute
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMolecular imagingPreclinical imagingImaging phantomIn vivoBiomedical engineeringMagnetic resonance imagingFluorescence-lifetime imaging microscopyEx vivoPositron emission tomographyOptical imagingMaterials scienceFluorescenceRadiologyMedicineOpticsBiologyPhysics

Abstract

fetched live from OpenAlex

Combining Fluorescent Molecular Tomography (FMT) with anatomical imaging, e.g. MRI facilitates interpreting functional information. Furthermore, using a heterogeneous model for light propagation has been shown in simulations to be superior to homogeneous modeling to quantify fluorescence. Here, we present a combined FMT-MRI system and apply it to heart and aorta molecular imaging, a challenging area due to strong tissue heterogeneity and the presence of air-voids due to lungs. First investigating performance in a phantom and mouse corpse, the MRI-enabled heterogeneous models resulted in an improved quantification of fluorescence reconstructions. The system was then used in mice for in vivo atherosclerosis molecular imaging. Results show that, when using the heterogeneous model, reconstructions were in agreement with the ex vivo measurements. Therefore, the proposed system might serve as a powerful imaging tool for atherosclerosis in mice.

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 score0.398
Threshold uncertainty score0.829

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 head0.010
GPT teacher head0.278
Teacher spread0.268 · 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