Title
Estimation of Tool Pose Based on Force-Density Correlation During Robotic Drilling.
Abstract
The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.
Year
DOI
Venue
2013
10.1109/TBME.2012.2235439
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
robotics,calibration,biology,pose estimation,otology,visual inspection,estimation,surgery,robotic surgery,force,algorithms,robots,accuracy,image registration,trajectory,neurophysiology
Computer vision,Visual inspection,Fiducial marker,Computer science,Correctness,Navigation system,Artificial intelligence,Robot,Drill,Calibration,Image registration
Journal
Volume
Issue
ISSN
60
4
0018-9294
Citations 
PageRank 
References 
14
1.25
1
Authors
7
Name
Order
Citations
PageRank
Tom M. Williamson1265.87
Brett J. Bell2203.59
Nicolas Gerber3449.79
Lilibeth Salas4141.58
Philippe Zysset5141.25
Marco Caversaccio65113.09
Stefan Weber73912.46