Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …

Image registration is a fundamental task in multiple medical image analysis applications.
With the advent of deep learning, there have been significant advances in algorithmic …

We propose to learn a low-dimensional probabilistic deformation model from data which can
be used for the registration and the analysis of deformations. The latent variable model …

We propose an efficient non-parametric diffeomorphic image registration algorithm based on
Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons …

Most medical image registration algorithms suffer from a directionality bias that has been
shown to largely impact subsequent analyses. Several approaches have been proposed in …

Importance Early identification of Alzheimer disease (AD) is important for clinical
management and affords the opportunity to assess potential disease-modifying agents in …

An overview of computational procedures for examining neuroanatomical variability is
presented. The review focuses on approaches that can be applied using the SPM software …

We propose a nonparametric, probabilistic model for the automatic segmentation of medical
images, given a training set of images and corresponding label maps. The resulting …

This paper introduces an unsupervised adversarial similarity network for image registration.
Unlike existing deep learning registration methods, our approach can train a deformable …

Detecting early morphological changes in the brain and making early diagnosis are
important for Alzheimer's disease (AD). High resolution magnetic resonance imaging can be …