Acceleration controlled diffeomorphisms for nonparametric image regression

James Fishbaugh, Guido Gerig

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

    Abstract

    The analysis of medical image time-series is becoming increasingly important as longitudinal imaging studies are maturing and large scale open imaging databases are becoming available. Image regression is widely used for several purposes: as a statistical representation for hypothesis testing, to bring clinical scores and images not acquired at the same time into temporal correspondence, or as a consistency filter to enforce temporal correlation. Geodesic image regression is the most prominent method, but the geodesic constraint limits the flexibility and therefore the application of the model, particularly when the observation time window is large or the anatomical changes are non-monotonic. In this paper, we propose to parameterize diffeomorphic flow by acceleration rather than velocity, as in the geodesic model. This results in a nonparametric image regression model which is completely flexible to capture complex change trajectories, while still constrained to be diffeomorphic and with a guarantee of temporal smoothness. We demonstrate the application of our model on synthetic 2D images as well as real 3D images of the cardiac cycle.

    Original languageEnglish (US)
    Title of host publicationISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
    PublisherIEEE Computer Society
    Pages1488-1491
    Number of pages4
    ISBN (Electronic)9781538636411
    DOIs
    StatePublished - Apr 2019
    Event16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy
    Duration: Apr 8 2019Apr 11 2019

    Publication series

    NameProceedings - International Symposium on Biomedical Imaging
    Volume2019-April
    ISSN (Print)1945-7928
    ISSN (Electronic)1945-8452

    Conference

    Conference16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
    CountryItaly
    CityVenice
    Period4/8/194/11/19

    Fingerprint

    Imaging techniques
    Time series
    Trajectories
    Longitudinal Studies
    Observation
    Databases
    Testing

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Radiology Nuclear Medicine and imaging

    Cite this

    Fishbaugh, J., & Gerig, G. (2019). Acceleration controlled diffeomorphisms for nonparametric image regression. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging (pp. 1488-1491). [8759583] (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ISBI.2019.8759583

    Acceleration controlled diffeomorphisms for nonparametric image regression. / Fishbaugh, James; Gerig, Guido.

    ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. p. 1488-1491 8759583 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2019-April).

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

    Fishbaugh, J & Gerig, G 2019, Acceleration controlled diffeomorphisms for nonparametric image regression. in ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging., 8759583, Proceedings - International Symposium on Biomedical Imaging, vol. 2019-April, IEEE Computer Society, pp. 1488-1491, 16th IEEE International Symposium on Biomedical Imaging, ISBI 2019, Venice, Italy, 4/8/19. https://doi.org/10.1109/ISBI.2019.8759583
    Fishbaugh J, Gerig G. Acceleration controlled diffeomorphisms for nonparametric image regression. In ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society. 2019. p. 1488-1491. 8759583. (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2019.8759583
    Fishbaugh, James ; Gerig, Guido. / Acceleration controlled diffeomorphisms for nonparametric image regression. ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, 2019. pp. 1488-1491 (Proceedings - International Symposium on Biomedical Imaging).
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