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Fast, robust, and accurate monocular peer-to-peer tracking for surgical navigation

  • Purpose This work presents a new monocular peer-to-peer tracking concept overcoming the distinction between tracking tools and tracked tools for optical navigation systems. A marker model concept based on marker triplets combined with a fast and robust algorithm for assigning image feature points to the corresponding markers of the tracker is introduced. Also included is a new and fast algorithmPurpose This work presents a new monocular peer-to-peer tracking concept overcoming the distinction between tracking tools and tracked tools for optical navigation systems. A marker model concept based on marker triplets combined with a fast and robust algorithm for assigning image feature points to the corresponding markers of the tracker is introduced. Also included is a new and fast algorithm for pose estimation. Methods A peer-to-peer tracker consists of seven markers, which can be tracked by other peers, and one camera which is used to track the position and orientation of other peers. The special marker layout enables a fast and robust algorithm for assigning image feature points to the correct markers. The iterative pose estimation algorithm is based on point-to-line matching with Lagrange–Newton optimization and does not rely on initial guesses. Uniformly distributed quaternions in 4D (the vertices of a hexacosichora) are used as starting points and always provide the global minimum. Results Experiments have shown that the marker assignment algorithm robustly assigns image feature points to the correct markers even under challenging conditions. The pose estimation algorithm works fast, robustly and always finds the correct pose of the trackers. Image processing, marker assignment, and pose estimation for two trackers are handled in less than 18 ms on an Intel i7-6700 desktop computer at 3.4 GHz. Conclusion The new peer-to-peer tracking concept is a valuable approach to a decentralized navigation system that offers more freedom in the operating room while providing accurate, fast, and robust results.show moreshow less

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Author:Simon StrzeletzORCiDGND, Simon HazubskiORCiDGND, José-Luis Moctezuma, Harald HoppeORCiDGND
Publisher:Springer
Year of Publication:2020
Language:English
Tag:pose estimation; surgical navigation; tracking
DDC classes:600 Technik, Medizin, angewandte Wissenschaften
Parent Title (English):International Journal of Computer Assisted Radiology and Surgery
Volume:15
Issue:3
ISSN:1861-6410 (Print)
ISSN:1861-6429 (Online)
First Page:479
Last Page:489
Document Type:Article (reviewed)
Open Access:Frei zugänglich
Institutes:Bibliografie
Release Date:2021/01/13
Licence (German):License LogoEs gilt das UrhG
URL:https://link.springer.com/article/10.1007%2Fs11548-019-02111-z
DOI:https://doi.org/10.1007/s11548-019-02111-z