<title>Assessment of temporal jitter in ECG gated dynamic three-dimensional echocardiography</title>
Bibliographic record
Abstract
Dynamic-3D echocardiography can potentially provide an accurate representation of the complex cardiac anatomy and dynamics over the cardiac cycle. However, the image quality of dynamic-3D echocardiography is limited by temporal jitter artifacts; which result from the asynchronous acquisition of video frames with respect to the cardiac cycle. In our study, we estimate the extent of temporal jitter in dynamic-3D echocardiography using in-vitro studies, and also provide a theoretical method to predict temporal jitter. Dynamic-3D images of a myocardial motion phantom were reconstructed and analyzed for cardiac wall motion at different heart rates. Our algorithm to quantify temporal jitter consisted of three steps. First, the distance of a reference plane to the surface of the phantom was computed and plotted as a 2D grayscale distance map in each 3D image. Second, surface variation maps were derived and finally, 2D jitter maps were plotted to provide a measure of temporal jitter in each 3D image at each cardiac phase. Temporal jitter was as large as 3.5 mm in peak systole and 1.5 mm in end diastole. The standard deviation in the jitter maps ranged from 0.5 mm in end-diastole to 1.0 mm in peak-systole; which agreed well with our theoretical analysis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".