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Semi‐autonomous image‐guided brain tumour resection using an integrated robotic system: A bench‐top study
Author(s) -
Hu Danying,
Gong Yuanzheng,
Seibel Eric J.,
Sekhar Laligam N.,
Hannaford Blake
Publication year - 2018
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1872
Subject(s) - computer science , artificial intelligence , robotic surgery , robotic arm , automation , modularity (biology) , invasive surgery , image guided surgery , robot , computer vision , surgery , medicine , engineering , mechanical engineering , biology , genetics
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.