Work

Path planning for semi-automated simulated robotic neurosurgery

Year: 2015

Type: conference-paper

Abstract: This paper considers the semi-automated robotic surgical procedure for removing the brain tumor margins, where the manual operation is a tedious and time-consuming task for surgeons. We present robust path planning methods for robotic ablation of tumor residues in various shapes, which are represented in point-clouds instead of analytical geometry. Along with the path plans, corresponding metrics are also delivered to the surgeon for selecting the optimal candidate in the automated robotic ablation. The selected path plan is then executed and tested on RAVEN™ II surgical robot platform as part of the semi-automated robotic brain tumor ablation surgery in a simulated tissue phantom.

Source: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

DOI: 10.1109/iros.2015.7353737

Authors: Danying Hu, Yuanzheng Gong, Blake Hannaford, Eric J. Seibel

Institution: University of Washington

Language: English

Topic: Soft Robotics and Applications

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering