Vision-Based Automatic Control of a Surgical Robot for Posterior Segment Ophthalmic Surgery

In ophthalmic surgery, especially in posterior segment procedures, clinicians face significant challenges, like the inherent tremor of the surgeon’s arm, restricted visibility, and heavy reliance on the surgeon’s skills for precise control of hand-held tools during micro-surgical movements. Automatic control of robotic-assisted ophthalmic surgical systems has the potential to overcome these challenges, simplifying complex surgical procedures. This paper proposes a novel image-guided automatic control method for an Ophthalmic micro-Surgical Robot (OmSR), specifically designed for posterior segment eye surgery. The method relies on forceps shadow tracking. The paper introduces a tip detection network (Net-SR), which accurately calculates the coordinates of the Tips of Surgical Forceps (ToSF) and Tips of Shadow (ToS) to enable automatic navigation. Additionally, through the Non-Uniform Rational B-Spline (NURBS) curve interpolation and speed look-ahead algorithm, dense and time-continuous data points are obtained to improve control accuracy and smoothness. The accuracy of the Net-SR network and motion of the ToSF, and the effectiveness of the proposed automatic controller are experimentally evaluated. Results demonstrate a significant 98.21% improvement in the Net-SR network accuracy over the normal keypoint detection network. The use of the speed look-ahead algorithm leads to a notable 41.7% improvement in optimal speed, and the ToSF successfully reaches the target lesion with vision-based navigation and no overscale motion. Note to Practitioners—The practical problem that motivated this research is the need for safer and more efficient surgical procedures, focusing on minimizing the risk of fundus tissue damage associated with intraoperative surgical instruments. To overcome challenges related to handheld and tele-operated control, we explore automatic control as a promising solution. In this paper, the tip of the instrument can consistently and accurately reach the target lesion with high precision and no overscale motion, allowing for deskilling of complex and repetitive tasks. This capability holds potential for the clinical needle insertion operation and membrane peeling operation. The proposed control methods can also be extended to other surgical procedures.