Statistical shape models for segmentation and structural analysis

Guido Gerig, Martin Styner, Gabor Székely

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

    Abstract

    Biomedical imaging of large patient populations, both cross-sectionally and longitudinally, is becoming a standard technique for noninvasive, in-vivo studies of the pathophysiology of diseases and for monitoring drug treatment. In radiation oncology, imaging and extraction of anatomical organ geometry is a routine procedure for therapy planning an monitoring, and similar procedures are vital for surgical planning and image-guided therapy. Bottlenecks of today's studies, often processed by labor-intensive manual region drawing, arc the lack of efficient, reliable tools for three-dimensional organ segmentation and for advanced morphologic characterization. This paper discusses current research and development focused towards building of statistical shape models, used for automatic model-based segmentation and for shape analysis and discrimination. We build statistical shape models which describe the geometric variability and image intensity characteristics of anatomical structures. New segmentations are obtained by model deformation driven by local image match forces and constrained by the training statistics. Two complimentary representations for 3D shape are discussed and compared, one based on global surface parametrization and a second one on medial manifold description. The discussion will be guided by presenting a most recent study to construct a statistical shape model of the caudate structure.

    Original languageEnglish (US)
    Title of host publication2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
    PublisherIEEE Computer Society
    Pages18-21
    Number of pages4
    ISBN (Electronic)078037584X
    DOIs
    StatePublished - Jan 1 2002
    EventIEEE International Symposium on Biomedical Imaging, ISBI 2002 - Washington, United States
    Duration: Jul 7 2002Jul 10 2002

    Publication series

    NameProceedings - International Symposium on Biomedical Imaging
    Volume2002-January
    ISSN (Print)1945-7928
    ISSN (Electronic)1945-8452

    Other

    OtherIEEE International Symposium on Biomedical Imaging, ISBI 2002
    CountryUnited States
    CityWashington
    Period7/7/027/10/02

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    ASJC Scopus subject areas

    • Biomedical Engineering
    • Radiology Nuclear Medicine and imaging

    Cite this

    Gerig, G., Styner, M., & Székely, G. (2002). Statistical shape models for segmentation and structural analysis. In 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings (pp. 18-21). [1029182] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2002-January). IEEE Computer Society. https://doi.org/10.1109/ISBI.2002.1029182