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

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to
overcome the fundamental limitations of individual modalities. Neuroimaging fusion can …

Introduction This study investigated the diagnostic and disease‐monitoring potential of
plasma biomarkers in mild cognitive impairment (MCI) and Alzheimer's disease (AD) …

We present VoxelMorph, a fast learning-based framework for deformable, pairwise medical
image registration. Traditional registration methods optimize an objective function for each …

This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …

Abstract The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing,
nationwide study of the effects of environmental influences on behavioral and brain …

Anxiety is a mental state characterized by an intense sense of tension, worry or
apprehension, relative to something adverse that might happen in the future. Researchers …

Image segmentation is an important task in many medical applications. Methods based on
convolutional neural networks attain state-of-the-art accuracy; however, they typically rely on …

Abstract Machine learning algorithms can be trained to estimate age from brain structural
MRI. The difference between an individual's predicted and chronological age, predicted age …

Loss-of-function TREM2 mutations strongly increase Alzheimer's disease (AD) risk. Trem2
deletion has revealed protective Trem2 functions in preclinical models of β-amyloidosis, a …