A two-level transfer function based method for heart display with vascular tissue and scar enhancement
Bibliographic record
Abstract
Procedural guidance using high-resolution, three-dimensional (3D) myocardial scar mapping may offer assistance in directing catheter ablation therapy aimed at eliminating re-entrant arrhythmic pathways. For the purpose of pre-procedural planning and intra-procedural guidance, determining the spatial relationship between myocardial scar, cardiac chambers and vascular structures is a crucial step towards the delivery of percutaneous, image-guided ablative therapies with minimal fluoroscopic support. An important part of such a procedure is the spatial structure display, during which the transfer function (TF) adjustment is a mandatory operation. However, the TF tuning is a time consuming process and it is still a challenge to achieve a uniform mapping rule for creating an optimized visual result. In this paper, we propose several image processing algorithms and a new two-level TF based classification technique to address this problem. Our method improves the user performance and the visual uniformity of the resultant cardiac images.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".