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 …

Automatic medical image segmentation is an unsolved problem that has captured the
attention of many researchers. The purpose of this survey is to identify a representative set of …

Recent studies on brain imaging analysis witnessed the core roles of machine learning
techniques in computer-assisted intervention for brain disease diagnosis. Of various …

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 …

Feature selection is a critical step in deformable image registration. In particular, selecting
the most discriminative features that accurately and concisely describe complex …

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 …

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 …

Structural magnetic resonance imaging (MRI) has been proven to be an effective tool for
Alzheimer's disease (AD) diagnosis. While conventional MRI-based AD diagnosis typically …

Human cortical folding is believed to correlate with cognitive functions. This likely correlation
may have something to do with why abnormalities of cortical folding have been found in …