Diffusion tensor imaging (DT‐MRI or DTI) is an emerging imaging modality whose
importance has been growing considerably. However, the processing of this type of data (ie …

In this work we present a new generalization of the geometric mean of positive numbers on
symmetric positive-definite matrices, called Log-Euclidean. The approach is based on two …

This paper is dedicated to the statistical analysis of the space of multivariate normal
distributions with an application to the processing of Diffusion Tensor Images (DTI). It relies …

Biological networks are commonly used in biomedical and healthcare domains to effectively
model the structure of complex biological systems with interactions linking biological entities …

In this paper we present a Riemannian framework for smoothing data that are constrained to
live in P(n), the space of symmetric positive-definite matrices of order n. We start by giving …

* A special volume devoted principally to therole of the late Sir Charles Oatley in the
development of the scanning electron microscopeings* It contains historical articles and …

We address the problem of the segmentation of cerebral white matter structures from
diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images …

Guided by empirically established connections between clinically important tissue properties
and diffusion tensor parameters, we introduce a framework for decomposing variations in …

Computations on tensors, ie symmetric positive definite real matrices in medical imaging,
appear in many contexts. In medical imaging, these computations have become common …

A process that assists with the identification of potential hydrocarbon deposits that includes
performing a structural interpretation of a three-dimensional seismic volume, transforming …