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2017 | Supplement | Buchkapitel

Prediction of the Progression of Subcortical Brain Structures in Alzheimer’s Disease from Baseline

verfasst von : Alexandre Bône, Maxime Louis, Alexandre Routier, Jorge Samper, Michael Bacci, Benjamin Charlier, Olivier Colliot, Stanley Durrleman, the Alzheimer’s Disease Neuroimaging Initiative

Erschienen in: Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics

Verlag: Springer International Publishing

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Abstract

We propose a method to predict the subject-specific longitudinal progression of brain structures extracted from baseline MRI, and evaluate its performance on Alzheimer’s disease data. The disease progression is modeled as a trajectory on a group of diffeomorphisms in the context of large deformation diffeomorphic metric mapping (LDDMM). We first exhibit the limited predictive abilities of geodesic regression extrapolation on this group. Building on the recent concept of parallel curves in shape manifolds, we then introduce a second predictive protocol which personalizes previously learned trajectories to new subjects, and investigate the relative performances of two parallel shifting paradigms. This design only requires the baseline imaging data. Finally, coefficients encoding the disease dynamics are obtained from longitudinal cognitive measurements for each subject, and exploited to refine our methodology which is demonstrated to successfully predict the follow-up visits.

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Metadaten
Titel
Prediction of the Progression of Subcortical Brain Structures in Alzheimer’s Disease from Baseline
verfasst von
Alexandre Bône
Maxime Louis
Alexandre Routier
Jorge Samper
Michael Bacci
Benjamin Charlier
Olivier Colliot
Stanley Durrleman
the Alzheimer’s Disease Neuroimaging Initiative
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-67675-3_10