Automated foveola localization in retinal 3D-OCT images using structural support vector machine prediction

Yu Ying Liu, Hiroshi Ishikawa, Mei Chen, Gadi Wollstein, Joel S. Schuman, James M. Rehg

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

    Abstract

    We develop an automated method to determine the foveola location in macular 3D-OCT images in either healthy or pathological conditions. Structural Support Vector Machine (S-SVM) is trained to directly predict the location of the foveola, such that the score at the ground truth position is higher than that at any other position by a margin scaling with the associated localization loss. This S-SVM formulation directly minimizes the empirical risk of localization error, and makes efficient use of all available training data. It deals with the localization problem in a more principled way compared to the conventional binary classifier learning that uses zero-one loss and random sampling of negative examples. A total of 170 scans were collected for the experiment. Our method localized 95.1% of testing scans within the anatomical area of the foveola. Our experimental results show that the proposed method can effectively identify the location of the foveola, facilitating diagnosis around this important landmark.

    Original languageEnglish (US)
    Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
    EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
    PublisherSpringer Verlag
    Pages307-314
    Number of pages8
    ISBN (Print)9783642334146
    DOIs
    StatePublished - 2012
    Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
    Duration: Oct 1 2012Oct 5 2012

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume7510 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
    CountryFrance
    CityNice
    Period10/1/1210/5/12

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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