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Longitudinal Growth Modeling of Discrete-Time Functions with Application to DTI Tract Evolution in Early Neurodevelopment

Institution:
1School of Computing, SCI Institute, University of Utah, Salt Lake City, UT, USA.
2INRIA-Asclepios project, Sophia Antipolis, France.
3Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
Publisher:
ISBI 2012
Publication Date:
Dec-2013
Journal:
Proc IEEE Int Symp Biomed Imaging.
Volume Number:
2012
Pages:
1945-1400
Citation:
Proc IEEE Int Symp Biomed Imaging. 2013 Dec; 2012:1945-1400.
PubMed ID:
24443681
PMCID:
PMC3892762
Keywords:
spatiotemporal modeling, growth functions, ongitudinal image data, diffusion tensor imaging, Early Brain Development
Appears in Collections:
NA-MIC
Sponsors:
P50 MH064065/MH/NIMH NIH HHS/United States
R01 HD055741/HD/NICHD NIH HHS/United States
R01 HD067731/HD/NICHD NIH HHS/United States
R01 MH070890/MH/NIMH NIH HHS/United States
R01 NS055754/NS/NINDS NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
Generated Citation:
Sharma A., Durrleman S., Gilmore J.H., Gerig G. Longitudinal Growth Modeling of Discrete-Time Functions with Application to DTI Tract Evolution in Early Neurodevelopment. Proc IEEE Int Symp Biomed Imaging. 2013 Dec; 2012:1945-1400. PMID: 24443681. PMCID: PMC3892762.
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We present a new framework for spatiotemporal analysis of parameterized functions attributed by properties of 4D longitudinal image data. Our driving application is the measurement of temporal change in white matter diffusivity of fiber tracts. A smooth temporal modeling of change from a discrete-time set of functions is obtained with an extension of the logistic growth model to time-dependent spline functions, capturing growth with only a few descriptive parameters. An unbiased template baseline function is also jointly estimated. Solution is demonstrated via energy minimization with an extension to simultaneous modeling of trajectories for multiple subjects. The new framework is validated with synthetic data and applied to longitudinal DTI from 15 infants. Interpretation of estimated model growth parameters is facilitated by visualization in the original coordinate space of fiber tracts.

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