In this study, we investigate multi-scale features extracted from baseline structural magnetic
resonance imaging (MRI) for classifying patients with mild cognitive impairment (MCI), who …

Neuroimaging measurements derived from magnetic resonance imaging provide important
information required for detecting changes related to the progression of mild cognitive …

The role of structural brain magnetic resonance imaging (MRI) is becoming more and more
emphasized in the early diagnostics of Alzheimer's disease (AD). This study aimed to assess …

In this work we use a large scale regularization approach based on penalized logistic
regression to automatically classify structural MRI images (sMRI) according to cognitive …

Automated structural magnetic resonance imaging (MRI) processing pipelines and different
multivariate techniques are gaining popularity for Alzheimer's disease (AD) research. We …

In recent years, several high-dimensional, accurate, and effective classification methods
have been proposed for the automatic discrimination of the subject between Alzheimer's …

Alzheimer's disease (AD) is an irreversible neurodegenerative brain disorder that degrades
the memory and cognitive ability in elderly people. The main reason for memory loss and …

Incorporating with machine learning technology, neuroimaging markers which extracted
from structural Magnetic Resonance Images (sMRI), can help distinguish Alzheimer's …

Mild Cognitive Impairment (MCI) is an intermediate stage between healthy and Alzheimer's
disease (AD). To enable early intervention it is important to identify the MCI subjects that will …

Background Mild cognitive impairment (MCI) is subtle cognitive decline with an estimated 10–
15% yearly conversion rate toward Alzheimer's disease (AD). It remains unexplored in brain …