Computer-guided Navigation System for an Accurate Electrode Insertion.
Bibliographic record
Abstract
Since radiofrequency ablation (RFA) therapy for liver tumor was established, it became a standard percutaneous therapy. However, after the first ablation microbubbles sometimes obstruct a clear observation of the tumor under ultrasound guidance, and despite multiple RFA, a part of the tumor may remain viable. To solve this problem we developed a computer-guided navigation system for an accurate electrode insertion. We used POLARISTM (Northern Digital Inc., Ontario, Canada) as the active optical tracking system. The POLARISTM allows us to determine the real time 3D positions of active markers. With this system we could determine the location and the direction of the RFA electrode and the distance from the tip of the electrode to the target, which were displayed on the PC monitor. We also investigated the accuracy of this system as a preliminary test for its clinical application. The primary error between the real and the theoretical target was 2.88mm. The first insertion error was 5.78±1.97mm and the second insertion error was 8.01±1.01mm. While some hardware improvements and more technical experience are needed for its clinical applications, this computer-guided navigation system will be of great help for an accurate electrode insertion, especially in case of unresectable liver tumors subjected to RFA.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".