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This paper addresses the use of robotic tissue manipulation in medical needle insertion procedures to improve targeting accuracy and to help avoid damaging sensitive tissues. To control these multiple, potentially competing objectives, we present a phased controller that operates one manipulator at a time using closed-loop imaging feedback. We present an automated procedure planning technique that uses tissue geometry to select the needle insertion location, manipulation locations, and controller parameters. The planner uses a stochastic optimization of a cost function that includes tissue stress and robustness to disturbances. We demonstrate the system on 2D tissues simulated with a mass-spring model, including a simulation of a prostate brachytherapy procedure. It can reduce targeting errors from more than 2 cm to less than 1 mm, and can also shift obstacles by over 1 cm to clear them away from the needle path.
Torabi et al. (Fri,) studied this question.