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Record W2086242446 · doi:10.1002/mrm.23157

Applications of stimulated echo correction to multicomponent <i>T</i><sub>2</sub> analysis

2011· article· en· W2086242446 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.

Bibliographic record

VenueMagnetic Resonance in Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlip angleVoxelReproducibilityHomogeneity (statistics)Coherence (philosophical gambling strategy)AlgorithmPhysicsNuclear magnetic resonanceComputer scienceMathematicsArtificial intelligenceStatisticsMagnetic resonance imaging

Abstract

fetched live from OpenAlex

We propose a multicomponent fitting algorithm for multiecho T(2) data which allows for correction of T(2) distributions in the presence of stimulated echoes. Tracking the population of spins in many coherence pathways via the iterated method of the Extended Phase Graph algorithm allows for accurate quantification of echo magnitudes. The resulting decay curves allow for correction of errors due to nonideal refocusing pulses as a result of inhomogeneities in the B(1) transmit field. Non-Negative Least Squares fitting is used to quantify the magnitude of T(2) components at various T(2) values. This method, allowing calculation of the T(2) distribution with simultaneous extraction of the refocusing pulse flip angle, requires no change to image acquisition procedures and no extra data input. Validation by means of both simulations and in vivo data shows excellent interscan reproducibility while vastly improving the accuracy of extracted T(2) parameters in voxels where poor B(1) homogeneity leads to refocusing pulse flip angles significantly less than 180°. Most notably, myelin water fraction values in these regions are found to have increased consistency and accuracy.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.749
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
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 head0.021
GPT teacher head0.302
Teacher spread0.280 · 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