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Motion-Guided Dual-Camera Tracker for Endoscope Tracking and Motion Analysis in a Mechanical Gastric Simulator

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arxiv 2403.05146 v4 pith:7N624IIU submitted 2024-03-08 cs.CV

classification cs.CV
keywords motiontrackingtrackeranalysisendoscopeproposeddual-cameramechanical
verification ladder T0 review T1 audit T2 compute T3 formal

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Flexible endoscope motion tracking and analysis in mechanical simulators have proven useful for endoscopy training. Common motion tracking methods based on electromagnetic tracker are however limited by their high cost and material susceptibility. In this work, the motion-guided dual-camera vision tracker is proposed to provide robust and accurate tracking of the endoscope tip's 3D position. The tracker addresses several unique challenges of tracking flexible endoscope tip inside a dynamic, life-sized mechanical simulator. To address the appearance variation and keep dual-camera tracking consistency, the cross-camera mutual template strategy (CMT) is proposed by introducing dynamic transient mutual templates. To alleviate large occlusion and light-induced distortion, the Mamba-based motion-guided prediction head (MMH) is presented to aggregate historical motion with visual tracking. The proposed tracker achieves superior performance against state-of-the-art vision trackers, achieving 42% and 72% improvements against the second-best method in average error and maximum error. Further motion analysis involving novice and expert endoscopists also shows that the tip 3D motion provided by the proposed tracker enables more reliable motion analysis and more substantial differentiation between different expertise levels, compared with other trackers. Project page: https://github.com/PieceZhang/MotionDCTrack

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. MrTrack: Register Mamba for Needle Tracking with Rapid Reciprocating Motion during Ultrasound-Guided Aspiration Biopsy

    cs.CV 2025-05 conditional novelty 6.0 of 10

    MrTrack combines Mamba-based feature extraction with a register bank for temporal memory, reaching 73.9 FPS and best accuracy on aspiration biopsy needle tracking.

  2. MambaXCTrack: Mamba-based Tracker with SSM Cross-correlation and Motion Prompt for Ultrasound Needle Tracking

    cs.CV 2024-11 conditional novelty 6.0 of 10

    MambaXCTrack introduces SSM-based cross-correlation with interleaved scanning and an implicit motion descriptor, and reports state-of-the-art ultrasound needle tracking accuracy on its own phantom and tissue dataset.

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