Real-Time Robust Simultaneous Catheter and Environment Modeling for Endovascular Navigation

Zhao, L; Giannarou, S; Lee, SL; Yang, GZ

Real-Time Robust Simultaneous Catheter and Environment Modeling for Endovascular Navigation

Zhao, L

Giannarou, S Lee, SL Yang, GZ

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Publisher:: Elsevier
Publication Type:: Chapter
Citation:: Intravascular Ultrasound: From Acquisition to Advanced Quantitative Analysis, 2020, pp. 185-197
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Zhao, L https://orcid.org/0000-0003-4063-8183
dc.contributor.author	Giannarou, S
dc.contributor.author	Lee, SL
dc.contributor.author	Yang, GZ
dc.date.accessioned	2023-01-05T23:06:52Z
dc.date.available	2023-01-05T23:06:52Z
dc.date.issued	2020-01-01
dc.identifier.citation	Intravascular Ultrasound: From Acquisition to Advanced Quantitative Analysis, 2020, pp. 185-197
dc.identifier.isbn	9780128188330
dc.identifier.uri	http://hdl.handle.net/10453/164730
dc.description.abstract	Due to the complexity in catheter control and navigation, endovascular procedures are characterized by significant challenges. Real-time recovery of the 3D structure of the vasculature intraoperatively is necessary to visualize the interaction between the catheter and its surrounding environment to facilitate catheter manipulations. Nonionizing imaging techniques such as intravascular ultrasound (IVUS) are increasingly used in vessel reconstruction approaches. To enable accurate recovery of vessel structures, this chapter presents a robust and real-time simultaneous catheter and environment modeling method for endovascular navigation based on IVUS imaging, electromagnetic (EM) sensing as well as the vessel structure information obtained from the preoperative CT/MR imaging. By considering the uncertainty in both the IVUS contour and the EM pose in the proposed nonlinear optimization problem, the proposed algorithm can provide accurate vessel reconstruction, at the same time deal with sensing errors and abrupt catheter motions. Experimental results using two different phantoms, with different catheter motions demonstrated the accuracy of the vessel reconstruction and the potential clinical value of the proposed vessel reconstruction method.
dc.format.extent	11
dc.language	en
dc.publisher	Elsevier
dc.relation	http://purl.org/au-research/grants/arc/DP200100982
dc.relation.ispartof	Intravascular Ultrasound: From Acquisition to Advanced Quantitative Analysis
dc.relation.isbasedon	10.1016/B978-0-12-818833-0.00011-4
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Real-Time Robust Simultaneous Catheter and Environment Modeling for Endovascular Navigation
dc.type	Chapter
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2023-01-05T23:06:50Z
pubs.place-of-publication	The Netherlands
pubs.publication-status	Published
dc.location	The Netherlands

Abstract:

Due to the complexity in catheter control and navigation, endovascular procedures are characterized by significant challenges. Real-time recovery of the 3D structure of the vasculature intraoperatively is necessary to visualize the interaction between the catheter and its surrounding environment to facilitate catheter manipulations. Nonionizing imaging techniques such as intravascular ultrasound (IVUS) are increasingly used in vessel reconstruction approaches. To enable accurate recovery of vessel structures, this chapter presents a robust and real-time simultaneous catheter and environment modeling method for endovascular navigation based on IVUS imaging, electromagnetic (EM) sensing as well as the vessel structure information obtained from the preoperative CT/MR imaging. By considering the uncertainty in both the IVUS contour and the EM pose in the proposed nonlinear optimization problem, the proposed algorithm can provide accurate vessel reconstruction, at the same time deal with sensing errors and abrupt catheter motions. Experimental results using two different phantoms, with different catheter motions demonstrated the accuracy of the vessel reconstruction and the potential clinical value of the proposed vessel reconstruction method.

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http://hdl.handle.net/10453/164730