Hierarchical guidewire tracking in fluoroscopic sequences

Peng Wang; Ying Zhu; Wei Zhang; Terrence Chen; Peter Durlak; Ulrich Bill; Dorin Comaniciu

doi:10.1117/12.812508

27 March 2009 Hierarchical guidewire tracking in fluoroscopic sequences

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

Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72591L (2009) https://doi.org/10.1117/12.812508
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

In this paper, we present a novel hierarchical framework of guidewire tracking for image-guided interventions. Our method can automatically and robustly track a guidewire in fluoroscopy sequences during interventional procedures. The method consists of three main components: learning based guidewire segment detection, robust and fast rigid tracking, and nonrigid guidewire tracking. Each component aims to handle guidewire motion at a specific level. The learning based segment detection identifies small segments of a guidewire at the level of individual frames, and provides unique primitive features for subsequent tracking. Based on identified guidewire segments, the rigid tracking method robustly tracks the guidewire across successive frames, assuming that a major motion of guidewire is rigid, mainly caused by the breathing motion and table movement. Finally, a non-rigid tracking algorithm is applied to finely deform the guidewire to provide accurate shape. The presented guidewire tracking method has been evaluated on a test set of 47 sequences with more than 1000 frames. Quantitative evaluation demonstrates that the mean tracking error on the guidewire body is less than 2 pixels. Therefore the presented guidewire tracking method has a great potential for applications in image guided interventions.

Citation Download Citation

Peng Wang, Ying Zhu, Wei Zhang, Terrence Chen, Peter Durlak, Ulrich Bill, and Dorin Comaniciu "Hierarchical guidewire tracking in fluoroscopic sequences", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72591L (27 March 2009); https://doi.org/10.1117/12.812508

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