An Ultrasound-Guided System for Autonomous Marking of Tumor Boundaries During Robot-assisted Surgery

While only a limited number of procedures have image guidance available during robotically guided surgery, they still require the surgeon to manually reference the obtained scans to their projected location on the tissue surface. While the surgeon may mark the boundaries on the organ surface via electrosurgery, the precise margin around the tumor is likely to remain variable and not guaranteed before a pathological analysis. This paper presents a first attempt to autonomously extract and mark tumor boundaries with a specified margin on the tissue surface. It presents a first concept for tool-tissue interaction control via imu sensor fusion and contact detection from the electrical signals of the *esu, requiring no force sensing. We develop and assess our approach on us phantoms with anatomical surface geometries, comparing different strategies for projecting the tumor onto the surface and assessing its accuracy in repeated trials. Finally, we demonstrate the feasibility of translating the approach to an ex-vivo porcine liver. We achieve mean true positive rates above 0.84 and false detection rates below 0.12 compared to a tracked reference for each calculation and execution of the marking trajectory for dummy and ex-vivo experiments.