DocumentCode :
3005065
Title :
Robust guidewire tracking in fluoroscopy
Author :
Peng Wang ; Chen, T. ; Ying Zhu ; Wei Zhang ; Zhou, S. Kevin ; Comaniciu, Dorin
Author_Institution :
Corp. Res., Integrated Data Syst. Dept., Siemens, Princeton, NJ, USA
fYear :
2009
fDate :
20-25 June 2009
Firstpage :
691
Lastpage :
698
Abstract :
A guidewire is a medical device inserted into vessels during image guided interventions for balloon inflation. During interventions, the guidewire undergoes non-rigid deformation due to patients´ breathing and cardiac motions, and such 3D motions are complicated when being projected onto the 2D fluoroscopy. Furthermore, in fluoroscopy there exist severe image artifacts and other wire-like structures. All these make robust guidewire tracking challenging. To address these challenges, this paper presents a probabilistic framework for robust guidewire tracking. We first introduce a semantic guidewire model that contains three parts, including a catheter tip, a guidewire tip and a guidewire body. Measurements of different parts are integrated into a Bayesian framework as measurements of a whole guidewire for robust guidewire tracking. Moreover, for each part, two types of measurements, one from learning-based detectors and the other from online appearance models, are applied and combined. A hierarchical and multi-resolution tracking scheme is then developed based on kernel-based measurement smoothing to track guidewires effectively and efficiently in a coarse-to-fine manner. The presented framework has been validated on a test set of 47 sequences, and achieves a mean tracking error of less than 2 pixels. This demonstrates the great potential of our method for clinical applications.
Keywords :
Bayes methods; image motion analysis; image resolution; medical image processing; radiography; smoothing methods; tracking; 2D fluoroscopy; 3D motions; Bayesian framework; balloon inflation; cardiac motions; coarse-to-fine manner; hierarchical tracking scheme; image artifacts; image guided interventions; kernel-based measurement smoothing; mean tracking error; medical device; multiresolution tracking scheme; non-rigid deformation; probabilistic framework; robust guidewire tracking; wire-like structures; Bayesian methods; Biomedical imaging; Catheters; Data systems; Detectors; Educational institutions; Noise robustness; Noise shaping; Smoothing methods; Tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on
Conference_Location :
Miami, FL
ISSN :
1063-6919
Print_ISBN :
978-1-4244-3992-8
Type :
conf
DOI :
10.1109/CVPR.2009.5206692
Filename :
5206692
Link To Document :
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