Tracking-by-Registration: A Robust Approach for Optical Tracking System in Surgical Navigation
Bibliographic record
Abstract
Optical tracking system (OTS) is an important part of surgical navigation and has been widely employed in clinical practice due to high accuracy and reliability. However, current OTS has a common occlusion of line-of-sight problem. To address the partial occlusion problem of target, we propose a tracking-by-registration (TbR) method based on a novel grid-based target (GT) and a corresponding target generation algorithm (TGA). Based on the word probability and target distance metric, TGA generates a set of GTs to minimize ambiguity. Utilizing the prior information of model sets, the identification of different targets is realized during tracking. An IR marker’s performance is theoretically evaluated and the maximum angles within the feasible range are validated. Both simulations and experiments have been carried out to validate the feasibility and performance of the proposed approach. The results indicate that the proposed approach has satisfactory performance to track the occluded target and provides a new option for optical tracking technologies.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".