Semi‐autonomous image‐guided brain tumour resection using an integrated robotic system: A bench‐top study

Abstract

BACKGROUND: Complete brain tumour resection is an extremely critical factor for patients' survival rate and long-term quality of life. This paper introduces a prototype medical robotic system that aims to automatically detect and clean up brain tumour residues after the removal of tumour bulk through conventional surgery. METHODS: We focus on the development of an integrated surgical robotic system for image-guided robotic brain surgery. The Behavior Tree framework is explored to coordinate cross-platform medical subtasks. RESULTS: The integrated system was tested on a simulated laboratory platform. Results and performance indicate the feasibility of supervised semi-automation for residual brain tumour ablation in a simulated surgical cavity with sub-millimetre accuracy. The modularity in the control architecture allows straightforward integration of further medical devices. CONCLUSIONS: This work presents a semi-automated laboratory setup, simulating an intraoperative robotic neurosurgical procedure with real-time endoscopic image guidance and provides a foundation for the future transition from engineering approaches to clinical application.