Noise Performance of a Precision Pulsed Electromagnet Power Supply for Magnetic Resonance Imaging
Bibliographic record
Abstract
Prepolarized magnetic resonance imaging (PMRI) uses two pulsed electromagnets to achieve high-field image quality with the benefits of low-field data acquisition. The principal challenge with all resistive MRI systems is the implementation of a highly precise magnet current supply. The noise current through the magnet is fundamentally limited by the current transducer used to provide feedback and the voltage reference used to generate the demand signal. Field instability in the main field magnet can both corrupt the received data and degrade the robustness of Carr¿Purcell¿Meiboom¿Gill (CPMG) echo trains, which are paramount to efficient imaging in PMRI. In this work, we present the magnet control system that achieved sufficient field stability for PMRI at $0.5/0.13$ T, identify the dominant sources of noise in the control system, examine the imaging artifacts that can occur if the field stability is insufficient, and identify how the design can be improved for better field stability, should it be required for future implementations of PMRI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".