2D/3D registration using only single-view fluoroscopy to guide cardiac ablation procedures: a feasibility study
Bibliographic record
Abstract
The CARTO XP is an electroanatomical cardiac mapping system that provides 3D color-coded maps of the electrical activity of the heart, however it is expensive and it can only use a single costly magnetic catheter for each patient intervention. Aim: To develop an affordable fluoroscopic navigation system that could shorten the duration of RF ablation procedures and increase its efficacy. Methodology: A 4-step filtering technique was implemented in order to project the tip electrode of an ablation catheter visible in single-view C-arm images in order to calculate its width. The width is directly proportional to the depth of the catheter. Results: For phantom experimentation, when displacing a 7- French catheter at 1cm intervals away from an X-ray source, the recovered depth using a single image was 2.05 ± 1.47 mm, whereas depth errors improved to 1.55 ± 1.30 mm when using an 8-French catheter. In clinic experimentation, twenty posterior and left lateral images of a catheter inside the left ventricle of a mongrel dog were acquired. The standard error of estimate for the recovered depth of the tip-electrode of the mapping catheter was 13.1 mm and 10.1 mm respectively for the posterior and lateral views. Conclusions: A filtering implementation using single-view C-arm images showed that it was possible to recover depth in phantom study and proved adequate in clinical experimentation based on isochronal map fusion results.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".