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RAUL: Reference-Assisted Ureteroscopy Localization for Skill Assessment
Not provided
skill assessmentcomputer visionmedical imagingtrajectory analysis
2609.19236
Builder Relevance
2h ago70%
Abstract
This work aims to recover ureteroscope trajectories from endoscopic video and derive navigation metrics to quantify differences in skill.
Reality Card
Core Claim
RAUL enables trajectory-based skill assessment of ureteroscopy navigation without additional tracking equipment, achieving a mean translation root mean square error of $0.5 \, \pm \, 0.1$ mm.
Method / Result
Increased frame-wise localization coverage from $50.5 \, \pm \, 14.9\%$ to $86.1 \, \pm \, 7.2\%$ of all video frames.
Limitations
The method has only been tested in phantoms, which may limit its applicability in real-world scenarios.
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