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 …

Functional localization is a concept which involves the application of a sequence of
geometrical and statistical image processing operations in order to define the location of …

For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …

In this paper, we propose a deep learning approach for image registration by predicting
deformation from image appearance. Since obtaining ground-truth deformation fields for …

Recently, there have been great interests for computer-aided diagnosis of Alzheimer's
disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous …

We describe the construction of a digital brain atlas composed of data from manually
delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal …

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

In this paper, we focus on joint regression and classification for Alzheimer's disease
diagnosis and propose a new feature selection method by embedding the relational …

Significance: Analysis of modern large-scale, multicenter or diseased data requires
deformable registration algorithms that can cope with data of diverse nature. Objective: We …

In this paper, we aim to predict conversion and time-to-conversion of mild cognitive
impairment (MCI) patients using multi-modal neuroimaging data and clinical data, via cross …