Detailed visualization of stents during their positioning and deployment is critical for the success of an interventional procedure. This paper presents a novel method that relies on balloon markers to enable real-time enhanced visualization and assessment of the stent positioning and expansion, together with the blood flow over the lesion area. The key novelty is an automatic tracking framework that includes a self-initialization phase based on the Viterbi algorithm and an online tracking phase implementing the Bayesian fusion of multiple cues. The resulting motion compensation stabilizes the image of the stent and by compounding multiple frames we obtain a much better stent contrast. Robust results are obtained from more than 350 clinical data sets.
CITATION STYLE
Chen, T., Wang, Y., Durlak, P., & Comaniciu, D. (2012). Real time assistance for stent positioning and assessment by self-initialized tracking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7510 LNCS, pp. 405–413). Springer Verlag. https://doi.org/10.1007/978-3-642-33415-3_50
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