Guidewire tracking during endovascular neurosurgery
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new method for guidewire tracking on fluoroscopic images from endovascular brain intervention. The combination of algorithms chosen can be implemented in real time, so that it can be used in an augmented reality 3D representation to assist physicians performing these interventions. A ribbon-like morphing process combined with a minimal path optimization algorithm is used to track lateral motion between successive frames. Forward motions are then tracked with an endpoint tracking algorithm, based on a circular window processed with the Radon transform. The proposed method was tested on 6 fluoroscopic sequences presenting high-speed motions, which were saved during endovascular brain interventions. The experiments showed above-average precision and robust guidewire tracking, without any permanent error requiring manual correction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it