Automatic detection of bioabsorbable coronary stents in IVUS images using a cascade of classifiers

David Rotger, Petia Radeva, Nico Bruining

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    13 Citations (Scopus)

    Abstract

    Bioabsorbable drug-eluting coronary stents present a very promising improvement to the common metallic ones solving some of the most important problems of stent implantation: the late restenosis. These stents made of poly-L-lactic acid cause a very subtle acoustic shadow (compared to the metallic ones) making difficult the automatic detection and measurements in images. In this paper, we propose a novel approach based on a cascade of GentleBoost classifiers to detect the stent struts using structural features to code the information of the different subregions of the struts. A stochastic gradient descent method is applied to optimize the overall performance of the detector. Validation results of struts detection are very encouraging with an average F -measure of 81%. © 2009 IEEE.
    Original languageEnglish
    Article number4801966
    Pages (from-to)535-537
    JournalIEEE Transactions on Information Technology in Biomedicine
    Volume14
    Issue number2
    DOIs
    Publication statusPublished - 1 Mar 2010

    Keywords

    • Automatic detection
    • Bioabsorbable
    • Cascade
    • GentleBoost
    • Intravascular ultrasound (IVUS)
    • Stent struts

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  • Cite this

    Rotger, D., Radeva, P., & Bruining, N. (2010). Automatic detection of bioabsorbable coronary stents in IVUS images using a cascade of classifiers. IEEE Transactions on Information Technology in Biomedicine, 14(2), 535-537. [4801966]. https://doi.org/10.1109/TITB.2009.2017528