A novel design methodology accounting for ramping and field inhomogeneities in dreMR imaging
Bibliographic record
Abstract
Delta relaxation enhanced magnetic resonance (dreMR) is a field cycled magnetic resonance imaging method for quantitative molecular imaging. DreMR uses an insertable field cycling coil to exploit longitudinal dispersion of contrast agents producing signal proportional to their concentration. Assumptions in the development of dreMR included instantaneous ramping of the insert coil and perfectly homogeneous field shifts. Here we discard these assumptions and show that finite ramping and field inhomogeneities can impair proportionality to agent concentration and produce significant signal from background tissues. To mitigate these effects, a novel dreMR coil design method is developed employing a boundary element method designed layer to the system which corrects field inhomogeneities, maximizing the usable dreMR imaging region. While a dreMR coil has not yet been constructed for use on humans, with these improvements it is expected that human designs will be much more feasible allowing the extension of this method to clinical studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".