Hierarchical guidewire tracking in fluoroscopic sequences

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7259, Issue , 2009, Pages

  Wang, Peng ^a   Zhu, Ying ^a   Zhang, Wei ^a   Chen, Terrence ^a   Durlak, Peter ^b   Bill, Ulrich ^b   Comaniciu, Dorin ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b SIEMENS AG   (Germany)

Author keywords

.uoroscopy; Deformation; Guidewire tracking; Image guided interventions; Performance evaluation

Indexed keywords

BREATHING MOTIONS; GUIDE-WIRE; GUIDE-WIRE TRACKING; IMAGE-GUIDED INTERVENTION; IMAGE-GUIDED INTERVENTIONS; INTERVENTIONAL PROCEDURES; MAIN COMPONENT; NON-RIGID TRACKING; PERFORMANCE EVALUATION; QUANTITATIVE EVALUATION; TABLE MOVEMENT; TEST SETS; TRACKING ERRORS; TRACKING METHOD;

DEFORMATION; FLUORESCENT SCREENS; IMAGE PROCESSING; IMAGING SYSTEMS;

MEDICAL IMAGING;

EID: 71749109263     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.812508     Document Type: Conference Paper

References (11)

1. Yilmaz, A., Javed, O., and Shah, M., "Object tracking: A survey," ACM Comput. Surv. 38(4), 13 (2006).
2. Kass, M., Witkin, A., and Terzopoulos, D., "Snakes: Active contour models," International Journal of Computer Vision 1(4), 321-331 (1987).
3. Shi, Y. and Karl, W. C., "Real-time tracking using level sets," in [IEEE Computer Society Conference on Computer Vision and Pattern Recognition], 2, 34-41, IEEE Computer Society, Washington, DC, USA (2005).
4. Palti-Wasserman, D., Brukstein, A. M., and Beyar, R., "Identifying and tracking a guide wire in the coronary arteriesduring angioplasty from x-ray images," IEEE Trans. Biomedical Engineering 44(2), 152-164 (1997).
5. Baert, S. A. M., Viergever, M. A., and Niessen,W. J., "Guide wire tracking during endovascular interventions," IEEE Trans. Med. Imaging 22(8), 965-972 (2003).
6. Barbu, A., Athitsos, V., Georgescu, B., Boehm, S., Durlak, P., and Comaniciu, D., "Hierarchical learning of curves application to guidewire localization in fluoroscopy," in [CVPR], (2007).
7. Tu, Z., "Probabilistic boosting-tree: Learning discriminative models for classification, recognition, and clustering," in [ICCV], 1589-1596 (2005).
8. Freund, Y. and Schapire, R. E., "A decision-theoretic generalization of on-line learning and an application to boosting," in [European Conference on Computational Learning Theory], 23-37 (1995).
9. Viola, P. and Jones, M., "Robust real-time object detection," Interntional Workshop on Statistical and Computational Theories of Vision 57(2), 137-154 (2004).
10. Friedman, J., Hastie, T., and Tibshirani, R., "Additive logistic regression: a statistical view of boosting," The Annals of Statistics 28(2), 337-374 (2000).
11. Mazouer, P., Chen, T., Zhu, Y., Wang, P., Durlak, P., Thiran, J.-P., and Comaniciu, D., "User-constrained guidewire localization in fluoroscopy," in [Medical Imaging: Image Processing], Proc. SPIE (2009).