Computational analysis of visual motion
Computational analysis of visual motion
International Journal of Computer Vision - Special issue on image-based servoing
Robot Control: The Task Function Approach
Robot Control: The Task Function Approach
A Modular Surgical Robotic System for Image Guided Percutaneous Procedures
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
A Single Image Registration Method for CT Guided Interventions
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
Pose reconstruction with an uncalibrated computed tomography imaging device
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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In this paper, we present a 3D-tracking technique inspired by visual servoing, specifically designed for Computed Tomography (CT). This work has been developed within the framework of robot- and computer-assisted interventional radiology, using stereotactic external fiducials made of radiopaque rods. These fiducials produce a set of image feature points that are used in a pose estimation algorithm, with only one slice. The patient's movements can then be tracked with the proposed algorithm by means of a motion field approach, so as to update the 2D/3D registration. Therefore, the proposed method solves a fundamental safety issue associated to the robotic assistance of CT-guided interventions. The contributions of the paper are threefold. First, the stereotactic visual feedback is modelled using the Plucker representation for 3D straight lines, while the CT plane slice provides corresponding image points. It is shown that the number of features needed to compute the pose is minimal compared to the known previous techniques. Second, the Jacobian matrix which relates the image points displacements to the velocity screw of the stereotactic frame is computed, providing the CT motion field. Third, the update of the Jacobian matrix is investigated. It requires the on-line stereotactic registration. As with the CT imaging modality, the 2D/3D registration is highly inaccurate when the fiducials are being moving, this paper provides a CT visual 3D tracking method inspired by the image-based visual servoing, which may alleviate the Jacobian matrix updates. To validate this technique, we first present simulations of the CT visual tracking. Finally, the proposed method is applied to real images obtained with stereotactic markers mounted on a robotic platform and placed in a CT scanner.