Abstract

The success rate of medical procedures involving needle insertion is often directly related to needle placement accuracy. Due to inherent limitations of commonly used freehand needle placement techniques, there is a need for a system providing for controlled needle steering for procedures that demand high positional accuracy. This paper describes a robotic system developed for flexible needle steering inside soft tissues under real-time ultrasound imaging. An inverse kinematics algorithm based on a virtual spring model is applied to calculate needle base manipulations required for the tip to follow a curved trajectory while avoiding physiological obstacles. The needle tip position is derived from ultrasound images and is used in calculations to minimize the tracking error, enabling a closed-loop needle insertion. In addition, as tissue stiffness is a necessary input to the control algorithm, a novel method to classify tissue stiffness from localized tissue displacements is proposed and shown to successfully distinguish between soft and stiff tissue. The system performance was experimentally verified by robotic manipulation of the needle base inside a phantom with layers of varying stiffnesses. The closed-loop experiment with updated tissue stiffness parameters demonstrated a needle-tip tracking error of approximately 1 mm and proved to be significantly more accurate than the freehand method.

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