Abstract
An intraluminal coronary stent is a metal scaffold deployed in a stenotic artery during Percutaneous Coronary Intervention (PCI). Intravascular Ultrasound (IVUS) is a catheter-based imaging technique generally used for assessing the correct placement of the stent. All the approaches proposed so far for the stent analysis only focused on the struts detection, while this paper proposes a novel approach to detect the boundaries and the position of the stent along the pullback. The pipeline of the method requires the identification of the stable frames of the sequence and the reliable detection of stent struts. Using this data, a measure of likelihood for a frame to contain a stent is computed. Then, a robust binary representation of the presence of the stent in the pullback is obtained applying an iterative and multi-scale approximation of the signal to symbols using the SAX algorithm. Results obtained comparing the automatic results versus the manual annotation of two observers on 80 IVUS in-vivo sequences shows that the method approaches the inter-observer variability scores.
S. Balocco and F. Ciompi equally contributed to the paper.
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Acknowledgements
This work was supported in part by the MICINN Grant TIN2015-66951-C2-1-R, SGR 1219, CERCA and ICREA Academia’2014.
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Balocco, S., Ciompi, F., Rigla, J., Carrillo, X., Mauri, J., Radeva, P. (2017). Intra-coronary Stent Localization in Intravascular Ultrasound Sequences, A Preliminary Study. In: Cardoso, M., et al. Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis. LABELS STENT CVII 2017 2017 2017. Lecture Notes in Computer Science(), vol 10552. Springer, Cham. https://doi.org/10.1007/978-3-319-67534-3_2
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