Motion-Guided Dual-Camera Tracker for Low-Cost Skill Evaluation of Gastric Endoscopy
CoRR(2024)
摘要
Gastric simulators with objective educational feedback have been proven
useful for endoscopy training. Existing electronic simulators with feedback are
however not commonly adopted due to their high cost. In this work, a
motion-guided dual-camera tracker is proposed to provide reliable endoscope tip
position feedback at a low cost inside a mechanical simulator for endoscopy
skill evaluation, tackling several unique challenges. To address the issue of
significant appearance variation of the endoscope tip while keeping dual-camera
tracking consistency, the cross-camera mutual template strategy (CMT) is
proposed to introduce dynamic transient mutual templates to dual-camera
tracking. To alleviate disturbance from large occlusion and distortion by the
light source from the endoscope tip, the Mamba-based motion-guided prediction
head (MMH) is presented to aggregate visual tracking with historical motion
information modeled by the state space model. The proposed tracker was
evaluated on datasets captured by low-cost camera pairs during endoscopy
procedures performed inside the mechanical simulator. The tracker achieves SOTA
performance with robust and consistent tracking on dual cameras. Further
downstream evaluation proves that the 3D tip position determined by the
proposed tracker enables reliable skill differentiation. The code and dataset
will be released upon acceptance.
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