Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …

Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …

Alzheimer's disease effects human brain cells and results in dementia. The gradual
deterioration of the brain cells results in disability of performing daily routine tasks. The …

Conclusion The application of machine learning methods to neuroimaging has risen more
rapidly than could have been predicted 15 years ago. It has been a very exciting new …

Effective and accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage
(ie, mild cognitive impairment (MCI)), has attracted more and more attention recently. So far …

Recently, several high dimensional classification methods have been proposed to
automatically discriminate between patients with Alzheimer's disease (AD) or mild cognitive …

This paper describes DARTEL, which is an algorithm for diffeomorphic image registration. It
is implemented for both 2D and 3D image registration and has been formulated to include …

The early identification of brain anatomy deviating from the normal pattern of growth and
atrophy, such as in Alzheimer's disease (AD), has the potential to improve clinical outcomes …

We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD)
from normal aging in individual scans. Recent advances in statistical learning theory have …