Self-adaptive asymmetric on-line boosting for detecting anatomical structures

Hong Wu, Nima Tajbakhsh, Wenzhe Xue, Jianming Liang

    Research output: Chapter in Book/Report/Conference proceedingConference contribution


    In this paper, we propose a self-adaptive, asymmetric on-line boosting (SAAOB) method for detecting anatomical structures in CT pulmonary angiography (CTPA). SAAOB is novel in that it exploits a new asymmetric loss criterion with self-adaptability according to the ratio of exposed positive and negative samples and in that it has an advanced rule to update sample's importance weight taking account of both classification result and sample's label. Our presented method is evaluated by detecting three distinct thoracic structures, the carina, the pulmonary trunk and the aortic arch, in both balanced and imbalanced conditions.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2012
    Subtitle of host publicationComputer-Aided Diagnosis
    StatePublished - Dec 1 2012
    EventMedical Imaging 2012: Computer-Aided Diagnosis - San Diego, CA, United States
    Duration: Feb 7 2012Feb 9 2012

    Publication series

    NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
    ISSN (Print)1605-7422


    OtherMedical Imaging 2012: Computer-Aided Diagnosis
    Country/TerritoryUnited States
    CitySan Diego, CA


    • And aortic arch
    • Asymmetric loss criterion
    • Balanced and imbalanced conditions
    • Carina
    • Pulmonary trunk
    • Self-Adaptive Asymmetric On-line Boosting (SAAOB)
    • Update sample's importance weight

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Atomic and Molecular Physics, and Optics
    • Radiology Nuclear Medicine and imaging


    Dive into the research topics of 'Self-adaptive asymmetric on-line boosting for detecting anatomical structures'. Together they form a unique fingerprint.

    Cite this