Abstract
We present an image-based navigation solution for a surgical robotic system with a Continuum Manipulator (CM). Our navigation system uses only fluoroscopic images from a mobile C-arm to estimate the CM shape and pose with respect to the bone anatomy. The CM pose and shape estimation is achieved using image intensity-based 2D/3D registration. A learning-based framework is used to automatically detect the CM in X-ray images, identifying landmark features that are used to initialize and regularize image registration. We also propose a modified hand-eye calibration method that numerically optimizes the hand-eye matrix during image registration. The proposed navigation system for CM positioning was tested in simulation and cadaveric studies. In simulation, the proposed registration achieved a mean error of 1.10±0.72 mm between the CM tip and a target entry point on the femur. In cadaveric experiments, the mean CM tip position error was 2.86±0.80 mm after registration and repositioning of the CM. The results suggest that our proposed fluoroscopic navigation is feasible to guide the CM in orthopedic applications.
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