On the Evaluation of Vorticity Using Cardiovascular Magnetic Resonance Velocity Measurements
Bibliographic record
Abstract
Vorticity and vortical structures play a fundamental role affecting the evaluation of energetic aspects (mainly left ventricle work) of cardiovascular function. Vorticity can be derived from cardiovascular magnetic resonance (CMR) imaging velocity measurements. However, several numerical schemes can be used to evaluate the vorticity field. The main objective of this work is to assess different numerical schemes used to evaluate the vorticity field derived from CMR velocity measurements. We compared the vorticity field obtained using direct differentiation schemes (eight-point circulation and Chapra) and derivate differentiation schemes (Richardson 4* and compact Richardson 4*) from a theoretical velocity field and in vivo CMR velocity measurements. In all cases, the effect of artificial spatial resolution up-sampling and signal-to-noise ratio (SNR) on vorticity computation was evaluated. Theoretical and in vivo results showed that the eight-point circulation method underestimated vorticity. Up-sampling evaluation showed that the artificial improvement of spatial resolution had no effect on mean absolute vorticity estimation but it affected SNR for all methods. The Richardson 4* method and its compact version were the most accurate and stable methods for vorticity magnitude evaluation. Vorticity field determination using the eight-point circulation method, the most common method used in CMR, has reduced accuracy compared to other vorticity schemes. Richardson 4* and its compact version showed stable SNR using both theoretical and in vivo data.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".