Two‐point water‐fat imaging with partially‐opposed‐phase (POP) acquisition: An asymmetric Dixon method
Why this work is in the frame
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Bibliographic record
Abstract
A novel two-point water-fat imaging method is introduced. In addition to the in-phase acquisition, water and fat magnetization vectors are sampled at partially-opposed-phase (POP) rather than exactly antiparallel as in the original Dixon method. This asymmetric sampling encodes more valuable phase information for identifying water and fat. From the magnitudes of the two complex images, a big and a small chemical component are first robustly obtained pixel by pixel and then used to form two possible error phasor candidates. The true error phasor is extracted from the two error phasor candidates through a simple procedure of regional iterative phasor extraction (RIPE). Finally, least-squares solutions of water and fat are obtained after the extracted error phasor is smoothed and removed from the complex images. For noise behavior, the effective number of signal averages NSA* is typically in the range of 1.87-1.96, very close to the maximum possible value of 2. Compared to earlier approaches, the proposed method is more efficient in data acquisition and straightforward in processing, and the final results are more robust. At both 1.5T and 0.3T, well separated and identified in vivo water and fat images covering a broad range of anatomical regions have been obtained, supporting the clinical utility of the method.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it