Abstract
This paper presents a robust and accurate vision-based augmented reality system for surgical navigation. The key point of our system is a robust and real-time monocular vision algorithm to estimate the 3D pose of surgical tools, utilizing specially designed code markers and Kalman filter-based position updating. The vision system is not impaired by occlusion and rapid change of illumination. The augmented reality system superimposes the 3D object wireframe onto the live viewing image taken from the surgical microscope as well as displaying other useful navigation information, while allowing the surgeons to freely change its zoom and focus for viewing. The experimental results verified the robustness and usefulness of the system, and acquired the image registration error less than 2 mm.
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