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<p>Computer-assisted interventions for enhanced experience in minimally invasive surgery (MIS) require motion tracking of the surgical instruments. This work presents a computationally efficient and marker-free method for tracking and visualizing 3D movements of surgical instruments in minimally invasive surgeries (MIS). Unlike existing deep-learning or marker-based systems, the proposed approach derives 3D motion directly from 2D segmentation maps using geometric and kinematic relations. The framework requires no physical modification to the instruments and can serve as a plug-in for existing surgical video datasets. Simulation and experimental validation using a motion capture system demonstrate high accuracy (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\le \)</EquationSource> </InlineEquation> 1&#xa0;mm translational error) and negligible orientation error, confirming the method’s reliability and simplicity for clinical integration.</p>

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From 2D to 3D surgical instrument tracking: a technique based on intervals and geometric cues

  • 期刊论文

  • 发表日期：

    2025年12月29日

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  • Shubhangi Nema,
  • Abhishek Mathur,
  • Leena Vachhani

摘要

Computer-assisted interventions for enhanced experience in minimally invasive surgery (MIS) require motion tracking of the surgical instruments. This work presents a computationally efficient and marker-free method for tracking and visualizing 3D movements of surgical instruments in minimally invasive surgeries (MIS). Unlike existing deep-learning or marker-based systems, the proposed approach derives 3D motion directly from 2D segmentation maps using geometric and kinematic relations. The framework requires no physical modification to the instruments and can serve as a plug-in for existing surgical video datasets. Simulation and experimental validation using a motion capture system demonstrate high accuracy ( \(\le \) 1 mm translational error) and negligible orientation error, confirming the method’s reliability and simplicity for clinical integration.