3D OCT retinal vessel segmentation based on boosting learning

Juan Xu, D. A. Tolliver, Hiroshi Ishikawa, Gadi Wollstein, Joel S. Schuman

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

    Abstract

    Blood vessel on retina is generally used for medical image registration. Three dimensional (3D) OCT is the new technique capable of providing the detailed 3D structure of retina. Most algorithms of 3D OCT vessel segmentation need to use the result of retinal layer segmentation to enhance vessel pattern. The proposed 3D boosting learning algorithm is an independent pixel (A-scan projection on OCT fundus image) classification algorithm, which does not rely on any processing result. Both 2D features from OCT fundus image and the third dimensional Haar-feature generated from each A-scan are used in the boosting learning. A matched template, second-order Gaussian filter is used to post-process the generated binary vessel image to clean up the false classifications and smooth the vessels. Eleven images were tested and compared with the manually marked reference. The average sensitivity and specificity were 85% and 88% respectively. The proposed algorithm is an efficient way to automatically identify the blood vessel on 3D OCT image without the need of pre-segmentation.

    Original languageEnglish (US)
    Title of host publicationWorld Congress on Medical Physics and Biomedical Engineering
    Subtitle of host publicationBiomedical Engineering for Audiology, Ophthalmology, Emergency and Dental Medicine
    Pages179-182
    Number of pages4
    Edition11
    DOIs
    StatePublished - Dec 1 2009
    EventWorld Congress on Medical Physics and Biomedical Engineering: Biomedical Engineering for Audiology, Ophthalmology, Emergency and Dental Medicine - Munich, Germany
    Duration: Sep 7 2009Sep 12 2009

    Publication series

    NameIFMBE Proceedings
    Number11
    Volume25
    ISSN (Print)1680-0737

    Conference

    ConferenceWorld Congress on Medical Physics and Biomedical Engineering: Biomedical Engineering for Audiology, Ophthalmology, Emergency and Dental Medicine
    CountryGermany
    CityMunich
    Period9/7/099/12/09

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    Keywords

    • 3D OCT
    • Boosting
    • Haar-feature
    • Pixel classification
    • Vessel segmentation

    ASJC Scopus subject areas

    • Bioengineering
    • Biomedical Engineering

    Cite this

    Xu, J., Tolliver, D. A., Ishikawa, H., Wollstein, G., & Schuman, J. S. (2009). 3D OCT retinal vessel segmentation based on boosting learning. In World Congress on Medical Physics and Biomedical Engineering: Biomedical Engineering for Audiology, Ophthalmology, Emergency and Dental Medicine (11 ed., pp. 179-182). (IFMBE Proceedings; Vol. 25, No. 11). https://doi.org/10.1007/978-3-642-03891-4-48