The main goal of surgical oncology is to achieve complete resection of cancerous tissue with minimal iatrogenic injury to the adjacent healthy structures. Brain tumour surgery is particularly demanding due to the eloquence of the tissue involved. There is evidence that increasing the extent of tumour resection substantially improves overall and progression-free survival. Realtime intraoperative tools which inform of residual disease are invaluable. Intraoperative Ultrasound (iUS) has been established as an efficient tool for tissue characterisation during brain tumour resection in neurosurgery.

The integration of iUS into the operating theatre is characterised by significant challenges related to the interpretation and quality of the US data. The capturing of high-quality US images requires substantial experience and visuo-tactile skills during manual operation. Recently, robotically-controlled US scanning systems have been proposed but the scanning of brain tissue poses major challenges to robotic systems because of the safety-critical nature of the procedure, the very low and precise contact forces required, the narrow access space and the large variety of tissue properties (hard scull, soft brain structure).

The aim of this paper is to introduce a robotic platform for autonomous iUS tissue scanning to optimise intraoperative diagnosis and improve surgical resection during robot-assisted operations. To guide anatomy specific robotic scanning and generate a representation of the robot task space, fast and accurate techniques for the recovery of 3D morphological structures of the surgical cavity are developed. The prototypic DLR MIRO surgical robotic arm is used to control the applied force and the in-plane motion of the US transducer. A key application of the proposed platform is the scanning of brain tissue to guide tumour resection.