Adaboost to classify plaque appearance in ivus images

Oriol Pujol, Petia Radeva, Jordi Vitrià, Josepa Mauri

    Research output: Contribution to journalArticleResearchpeer-review

    7 Citations (Scopus)

    Abstract

    Intravascular Ultrasound images represent a unique tool to analyze the morphological vessel structures and make decisions about plaque presence. Texture analysis is a robust way to detect and characterize different kind of vessel plaques. In this article, we make exhaustive comparison between different feature spaces to optimally describe plaque appearance and show that applying advanced classification techniques based on multiple classifiers (adaboost) significantly improves the final results. The validation tests on different kind of plaques are very encouraging. © Springer-Verlag 2004.
    Original languageEnglish
    Pages (from-to)629-636
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3287
    Publication statusPublished - 1 Dec 2004

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