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 …

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 …

A general-purpose deformable registration algorithm referred to as “DRAMMS” is presented
in this paper. DRAMMS bridges the gap between the traditional voxel-wise methods and …

The high-dimensional pattern classification methods, eg, support vector machines (SVM),
have been widely investigated for analysis of structural and functional brain images (such as …

Accurate prediction of clinical changes of mild cognitive impairment (MCI) patients, including
both qualitative change (ie, conversion to Alzheimer's disease (AD)) and quantitative …

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

Evaluating various algorithms for the inter-subject registration of brain magnetic resonance
images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated …

Intensity normalization is an important pre-processing step in the study and analysis of
Magnetic Resonance Images (MRI) of human brains. As most parametric supervised …

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 …