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Content Provider | IEEE Xplore Digital Library |
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Author | Wen Wu Chen, T. Barbu, A. Peng Wang Strobel, N. Zhou, S.K. Comaniciu, D. |
Copyright Year | 2011 |
Description | Author affiliation: Siemens AG, Forchheim, Germany (Comaniciu, D.) || Image Analytics and Informatics, Siemens Corporate Research, Princeton, NJ 08540, USA (Wen Wu; Chen, T.; Barbu, A.; Peng Wang; Strobel, N.) || Department of Statistics, Florida State University, Tallahassee, FL 32306, USA (Zhou, S.K.) |
Abstract | Catheter tracking has become more and more important in recent interventional applications. It provides real time navigation for the physicians and can be used to control a motion compensated fluoro overlay reference image for other means of guidance, e.g. involving a 3D anatomical model. Tracking the coronary sinus (CS) catheter is effective to compensate respiratory and cardiac motion for 3D overlay navigation to assist positioning the ablation catheter in Atrial Fibrillation (Afib) treatments. During interventions, the CS catheter performs rapid motion and non-rigid deformation due to the beating heart and respiration. In this paper, we model the CS catheter as a set of electrodes. Novelly designed hypotheses generated by a number of learning-based detectors are fused. Robust hypothesis matching through a Bayesian framework is then used to select the best hypothesis for each frame. As a result, our tracking method achieves very high robustness against challenging scenarios such as low SNR, occlusion, foreshortening, non-rigid deformation, as well as the catheter moving in and out of ROI. Quantitative evaluation has been conducted on a database of 13221 frames from 1073 sequences. Our approach obtains 0.50mm median error and 0.76mm mean error. 97.8% of evaluated data have errors less than 2.00mm. The speed of our tracking algorithm reaches 5 frames-per-second on most data sets. Our approach is not limited to the catheters inside the CS but can be extended to track other types of catheters, such as ablation catheters or circumferential mapping catheters. |
Starting Page | 1097 |
Ending Page | 1104 |
File Size | 2051696 |
Page Count | 8 |
File Format | |
ISBN | 9781457703942 |
ISSN | 10636919 |
e-ISBN | 9781457703959 |
DOI | 10.1109/CVPR.2011.5995553 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-06-20 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Catheters Electrodes Shape Tracking Detectors Polynomials Approximation methods |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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