Both normal aging and neurodegenerative diseases such as Alzheimer's disease cause morphological changes of the brain. To better distinguish between normal and abnormal cases, it is necessary to model changes in brain morphology owing to normal aging. To this end, we developed a method for analyzing and visualizing these changes for the entire brain morphology distribution in the general aging population. The method is applied to 1000 subjects from a large population imaging study in the elderly, from which 900 were used to train the model and 100 were used for testing. The results of the 100 test subjects show that the model generalizes to subjects outside the model population. Smooth percentile curves showing the brain morphology changes as a function of age and spatiotemporal atlases derived from the model population are publicly available via an interactive web application at agingbrain.bigr.nl.

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Keywords LMS method, Non-rigid groupwise registration, Partial least squares regression, Spatiotemporal atlas, Statistical modeling
Persistent URL dx.doi.org/10.1117/12.2207228, hdl.handle.net/1765/96316
Conference Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
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Citation
Huizinga, W, Poot, D.H.J, Roshchupkin, G.V, Bron, E.E, Ikram, M.A, Vernooij, M.W, … Klein, S. (2016). Modeling the brain morphology distribution in the general aging population. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. doi:10.1117/12.2207228