Problem
Research questions and friction points this paper is trying to address.
image-guided surgery
optical tracking
occlusion resilience
low-cost
surgical navigation
LARK: A Low-Cost, Accurate, Occlusion-Resilient, Kalman Filter-Assisted Tracking System for Image-Guided Surgery
🤖 AI Summary
This study addresses the high cost and occlusion vulnerability of commercial infrared tracking systems in image-guided surgery by proposing an open-source, multi-camera RGB-based optical tracking system. The proposed approach replaces expensive infrared hardware with a low-cost RGB camera array, achieving spatial localization through multi-view triangulation combined with monocular pose fusion. Additionally, adaptive Kalman filtering is introduced to enhance dynamic tracking robustness. Experimental results demonstrate that the system attains a point localization accuracy of 0.64 mm at a total hardware cost below $1,000. Furthermore, it exhibits graceful degradation under partial camera failure, significantly improving resilience to occlusion.
📝 Abstract
Image-guided surgery (IGS) depends on accurate tracking of surgical instruments to provide real-time navigation relative to anatomical structures. Commercial stereo infrared trackers are accurate but prone to occlusion and cost-prohibitive for many settings. This work presents LARK, a multi-camera optical tracking system using commodity RGB hardware and multi-view redundancy and fusion. We develop and evaluate two complete tracking methods: multi-view monocular pose fusion and multi-view triangulation. Both methods are assessed under varying occlusion levels using a precision-machined grid and an anatomical head phantom, and compared against a gold-standard stereo infrared system. With five cameras and adaptive Kalman filtering, LARK achieves median target registration errors of 0.64 mm for point localization with triangulation and 0.73 mm for trajectory tracking with pose fusion on the machined grid. Camera-subset experiments show graceful degradation in adaptive pose-fusion accuracy as fewer views remain available. With tracking hardware costing under $1,000 USD, LARK provides a low-cost platform for image-guided surgery research. Hardware designs and software are publicly available at https://nist.mni.mcgill.ca/software/ , and datasets at https://nist.mni.mcgill.ca/data/ .
Innovation
Methods, ideas, or system contributions that make the work stand out.
Multi-view Fusion
Kalman Filter
Occlusion-Resilient Tracking
Low-Cost RGB Hardware
Image-Guided Surgery
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