Evaluation of multicoil breast arrays for parallel imaging
Bibliographic record
Abstract
PURPOSE: To evaluate three multicoil breast arrays for both conventional and SENSE-accelerated imaging. MATERIALS AND METHODS: Two commercially available 8-element coils and a prototype 16-element coil were compared. One 8-element array had adjustable coils located next to the breast tissue and the other had a fixed coil arrangement; both were designed to allow parallel imaging in the left-right direction. The 16-element coil was designed to have coil sensitivity variation in both the left-right and superior-inferior directions, and also had adjustable coils. Their performance was assessed in terms of signal-to-noise ratio (SNR), g-factor, and uniformity with a custom-built phantom. RESULTS: The 16-element array with adjustable coils provided the highest SNR, while the 8-element coil with a fixed coil arrangement had the best uniformity. All coils performed well for SENSE acceleration in the left-right direction. The 8-element coils did not have the capability for acceleration in the superior-inferior direction across the whole volume. The 16-element coil enabled acceleration in the superior-inferior direction in addition to the left-right direction. CONCLUSION: Smaller, adjustable coil elements located next to breast tissue can provide greater SNR than larger, fixed coil elements. A multicoil breast array with high intrinsic SNR and low g-factors enables high-quality parallel imaging.
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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 | 0.001 | 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".