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Record W2151071618 · doi:10.1002/mrm.20317

Analytical approach to noncircular section birdcage coil design: Verification with a Cassinian oval coil

2004· article· en· W2151071618 on OpenAlexaff
Nicola De Zanche, Atiyah Yahya, Fred E. Vermeulen, Peter S. Allen

Bibliographic record

VenueMagnetic Resonance in Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsElectromagnetic coilRadiofrequency coilHomogeneity (statistics)Nuclear magnetic resonanceResonatorPhysicsQuadrature (astronomy)AcousticsOpticsComputer science

Abstract

fetched live from OpenAlex

A general analytical framework is presented for the design of birdcage radiofrequency resonators on cylindrical formers having arbitrary cross-sectional shape. The primary objective of such shapes would be to improve the sensitivity of the NMR experiment to noncircular regions of the human anatomy while maintaining field homogeneity and quadrature polarization comparable to those of standard circular birdcage coils. The shape of the corresponding radiofrequency screen, which is required to decouple the coil from the rest of the NMR system and which is key to the performance, is also provided by this methodology. The theory was tested by constructing a 3-T, quadrature, proton coil on a shape conforming to the anthropomorphic mean of the human head, namely, the oval of Cassini. Both bench tests (Q) and in vivo spectral and imaging comparisons of the Cassinian coil with an equivalently dimensioned and constructed circular birdcage coil, respectively, predicted and demonstrated in vivo an improvement in SNR of approximately 24% over the circular section coil. The experimental RF field homogeneity and quadrature performance were comparable for both coil geometries, with the circular coil being marginally superior.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.314
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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
Published2004
Admission routes1
Has abstractyes

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