Semi‐autonomous image‐guided brain tumour resection using an integrated robotic system: A bench‐top study. Issue 1 (3rd November 2017) - Hu, Danying; Gong, Yuanzheng; Seibel, Eric J.; Sekhar, Laligam N.; Hannaford, Blake
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.