A framework for longitudinal data analysis via shape regression

James Fishbaugh, Stanley Durrleman, Joseph Piven, Guido Gerig

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

    Abstract

    Traditional longitudinal analysis begins by extracting desired clinical measurements, such as volume or head circumference, from discrete imaging data. Typically, the continuous evolution of a scalar measurement is estimated by choosing a 1D regression model, such as kernel regression or fitting a polynomial of fixed degree. This type of analysis not only leads to separate models for each measurement, but there is no clear anatomical or biological interpretation to aid in the selection of the appropriate paradigm. In this paper, we propose a consistent framework for the analysis of longitudinal data by estimating the continuous evolution of shape over time as twice differentiable flows of deformations. In contrast to 1D regression models, one model is chosen to realistically capture the growth of anatomical structures. From the continuous evolution of shape, we can simply extract any clinical measurements of interest. We demonstrate on real anatomical surfaces that volume extracted from a continuous shape evolution is consistent with a 1D regression performed on the discrete measurements. We further show how the visualization of shape progression can aid in the search for significant measurements. Finally, we present an example on a shape complex of the brain (left hemisphere, right hemisphere, cerebellum) that demonstrates a potential clinical application for our framework.

    Original languageEnglish (US)
    Title of host publicationMedical Imaging 2012
    Subtitle of host publicationImage Processing
    DOIs
    StatePublished - May 14 2012
    EventMedical Imaging 2012: Image Processing - San Diego, CA, United States
    Duration: Feb 6 2012Feb 9 2012

    Publication series

    NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
    Volume8314
    ISSN (Print)1605-7422

    Other

    OtherMedical Imaging 2012: Image Processing
    CountryUnited States
    CitySan Diego, CA
    Period2/6/122/9/12

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Biomaterials
    • Atomic and Molecular Physics, and Optics
    • Radiology Nuclear Medicine and imaging

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  • Cite this

    Fishbaugh, J., Durrleman, S., Piven, J., & Gerig, G. (2012). A framework for longitudinal data analysis via shape regression. In Medical Imaging 2012: Image Processing [83143K] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 8314). https://doi.org/10.1117/12.911721