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Record W2774748041 · doi:10.1002/cmr.b.21359

Another alternate integrated circuit approach to modulation of radiofrequency transmission signals in magnetic resonance imaging

2017· article· en· W2774748041 on OpenAlexafffund
Benson P. Yang, Fred Tam, Clare E. McElcheran, Simon J. Graham

Bibliographic record

VenueConcepts in Magnetic Resonance Part B · 2017
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationSunnybrook Research Institute
KeywordsModulation (music)Computer scienceTransmission (telecommunications)Channel (broadcasting)SIGNAL (programming language)Electronic engineeringTelecommunicationsEngineeringPhysicsAcoustics

Abstract

fetched live from OpenAlex

Abstract Parallel radiofrequency transmission has garnered much attention for its wide range of benefits in magnetic resonance imaging (MRI), including reduced power deposition and radiofrequency excitation with improved spatial uniformity. However, few pTx systems are commercially available and most are expensive. This manuscript introduces another alternative parallel transmit architecture at 3 T based on field‐programmable gate array technology, and explores the utility of a low cost, integrated circuit approach to signal modulation that is easily scaled to high channel counts. The technical and engineering specifications of a complete 4‐channel signal modulation module are presented in detail, including radiofrequency characterization and MRI results. The experimental results are additionally compared to a commercially available 4‐channel modulation system. The findings indicate that the proposed device is easy to use, provides fine control of phase and amplitude on existing MRI systems, and can be fabricated for approximately 30 USD per channel. Initial estimates suggest that the complete 4‐channel modulation system (including the required software licenses and multi‐function reconfigurable input/output devices) can be implemented for approximately 10 000 USD.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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