Background The aim of this study was to investigate the diagnostic value of ML techniques
based on sMRI or/and fMRI for ADHD. Methods We conducted a comprehensive search …

Constructing generative models for functional observations is an important task in statistical
functional analysis. In general, functional data contains both phase (or x or horizontal) and …

We provide an overview of several shape space models that have been proposed in the
past few years, focusing, in particular on models involving Riemannian manifolds of shapes …

Background Motivated by an inconsistency between reports of high diagnosis-classification
accuracies and known heterogeneity in attention-deficit/hyperactivity disorder (ADHD), this …

In this paper we define a new methodology for shape analysis of parameterized surfaces,
where the main issues are:(1) choice of metric for shape comparisons and (2) invariance to …

This paper presents a novel Riemannian framework for shape analysis of parameterized
surfaces. In particular, it provides efficient algorithms for computing geodesic paths which, in …

This paper introduces a general setting for the construction of data fidelity metrics between
oriented or non-oriented geometric shapes like curves, curve sets or surfaces. These metrics …

Metrics on shape spaces are used to describe deformations that take one shape to another,
and to define a distance between shapes. We study a family of metrics on the space of …

An in-depth description of the state-of-the-art of 3D shape analysis techniques and their
applications This book discusses the different topics that come under the title of" 3D shape …

There has been increasing interest in jointly studying structural connectivity (SC) and
functional connectivity (FC) derived from diffusion and functional MRI. Previous connectome …