4D continuous medial representation by geodesic shape regression

Sungmin Hong, James Fishbaugh, Guido Gerig

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

    Abstract

    Longitudinal shape analysis has shown great potential to model anatomical processes from baseline to follow-up observations. Shape regression estimates a continuous trajectory of time-discrete anatomical shapes to quantify temporal changes. The need for shape alignment and point-to-point correspondences represent limitations of current shape analysis methodologies, and present significant challenges in shape evaluation. We propose a method that estimates a continuous trajectory of continuous medial representations (CM-Rep) from a set of time-discrete observed shapes. To avoid the traditional step of aligning individual objects, shape changes are modeled via diffeomorphic ambient space deformations. Using a medial shape representation, we separately capture object pose changes and intrinsic geometry changes. Tests and validation with synthetic and real anatomical shapes demonstrate that the new method captures extrinsic shape changes as well as intrinsic shape changes encoded with CM-Reps, a highly relevant property for studying growth and disease processes.

    LanguageEnglish (US)
    Title of host publication2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
    PublisherIEEE Computer Society
    Pages1014-1017
    Number of pages4
    Volume2018-April
    ISBN (Electronic)9781538636367
    DOIs
    StatePublished - May 23 2018
    Event15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States
    Duration: Apr 4 2018Apr 7 2018

    Other

    Other15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
    CountryUnited States
    CityWashington
    Period4/4/184/7/18

    Fingerprint

    Trajectories
    Anatomic Models
    Geometry
    Growth

    Keywords

    • Brain
    • Modeling - Anatomical
    • Physiological and pathological
    • Shape Analysis

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Radiology Nuclear Medicine and imaging

    Cite this

    Hong, S., Fishbaugh, J., & Gerig, G. (2018). 4D continuous medial representation by geodesic shape regression. In 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018 (Vol. 2018-April, pp. 1014-1017). IEEE Computer Society. https://doi.org/10.1109/ISBI.2018.8363743

    4D continuous medial representation by geodesic shape regression. / Hong, Sungmin; Fishbaugh, James; Gerig, Guido.

    2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. Vol. 2018-April IEEE Computer Society, 2018. p. 1014-1017.

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

    Hong, S, Fishbaugh, J & Gerig, G 2018, 4D continuous medial representation by geodesic shape regression. in 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. vol. 2018-April, IEEE Computer Society, pp. 1014-1017, 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, United States, 4/4/18. https://doi.org/10.1109/ISBI.2018.8363743
    Hong S, Fishbaugh J, Gerig G. 4D continuous medial representation by geodesic shape regression. In 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. Vol. 2018-April. IEEE Computer Society. 2018. p. 1014-1017 https://doi.org/10.1109/ISBI.2018.8363743
    Hong, Sungmin ; Fishbaugh, James ; Gerig, Guido. / 4D continuous medial representation by geodesic shape regression. 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. Vol. 2018-April IEEE Computer Society, 2018. pp. 1014-1017
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