SCEM+: real-time robust simultaneous catheter and environment modeling for endovascular navigation
File(s)RA-L_Liang_20160128.pdf (5.18 MB)
Accepted version
Author(s)
Zhao, L
Giannarou, S
Lee, S
Yang, GZ
Type
Conference Paper
Abstract
Endovascular procedures are characterised by significant challenges mainly due to the complexity in catheter control and navigation. Real-time recovery of the 3-D structure of the vasculature is necessary to visualise the interaction between the catheter and its surrounding environment to facilitate catheter manipulations. State-of-the-art intraoperative vessel reconstruction approaches are increasingly relying on nonionising imaging techniques such as optical coherence tomography (OCT) and intravascular ultrasound (IVUS). To enable accurate recovery of vessel structures and to deal with sensing errors and abrupt catheter motions, this letter presents a robust and real-time vessel reconstruction scheme for endovascular navigation based on IVUS and electromagnetic (EM) tracking. It is formulated as a nonlinear optimisation problem, which considers the uncertainty in both the IVUS contour and the EM pose, as well as vessel morphology provided by preoperative data. Detailed phantom validation is performed and the results demonstrate the potential clinical value of the technique.
Date Issued
2016-07-01
Date Acceptance
2016-01-16
Citation
IEEE Robotics and Automation Letters, 2016, 1 (2), pp.961-968
ISSN
2377-3766
Publisher
Institute of Electrical and Electronics Engineers
Start Page
961
End Page
968
Journal / Book Title
IEEE Robotics and Automation Letters
Volume
1
Issue
2
Is Replaced By
Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Katholieke Universiteit Leuven
Grant Number
CASCADE - 601021
Source
IEEE International Conference on Robotics and Automation
Publication Status
Published
Start Date
2016-05-16
Finish Date
2016-05-21
Coverage Spatial
Stockholm, Sweden
Date Publish Online
2016-02-03