Data-driven disease progression models are an emerging set of computational tools that
reconstruct disease timelines for long-term chronic diseases, providing unique insights into …

The Precision Neurology development process implements systems theory with system
biology and neurophysiology in a parallel, bidirectional research path: a combined …

This paper develops the theory of geodesic regression and least-squares estimation on
Riemannian manifolds. Geodesic regression is a method for finding the relationship …

In the context of large deformations by diffeomorphisms, we propose a new diffeomorphic
registration algorithm for 3D images that performs the optimization directly on the set of …

Cross-sectional analysis of longitudinal anatomical magnetic resonance imaging (MRI) data
may be suboptimal as each dataset is analyzed independently. In this study, we evaluate …

After intense scientific exploration and more than a decade of failed trials, Alzheimer's
disease (AD) remains a fatal global epidemic. A traditional research and drug development …

In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization,
analysis, visualization, and comparison of results across individuals and different studies …

This paper proposes an original approach for the statistical analysis of longitudinal shape
data. The proposed method allows the characterization of typical growth patterns and …

This paper presents a new registration algorithm, called Temporal Diffeomorphic Free Form
Deformation (TDFFD), and its application to motion and strain quantification from a …

Registration of image-time series has so far been accomplished (i) by concatenating
registrations between image pairs,(ii) by solving a joint estimation problem resulting in …