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

Objectives This article aimed to carry out a narrative literature review of early diagnostic
markers of Alzheimer's disease (AD) based on both micro and macro levels of pathology …

Multi-modal medical imaging information has been widely used in computer-assisted
investigations and diagnoses. A typical example is that the combination of information from …

Alzheimer's disease (AD) has become a serious hazard to human health in recent years,
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …

Alzheimer's disease (AD) is an irreversible brain disease that severely damages human
thinking and memory. Early diagnosis plays an important part in the prevention and …

Alzheimer's disease (AD) is a progressive neurodegenerative disease, and mild cognitive
impairment (MCI) is a transitional stage between normal control (NC) and AD. A multiclass …

Background Alzheimer's disease, the most common cause of dementia, causes a
progressive and irreversible deterioration of cognition that can sometimes be difficult to …

Objective To evaluate the diagnostic performance of hippocampal volumetry for Alzheimer's
disease (AD) or mild cognitive impairment (MCI). Methods The MEDLINE and Embase …

Background: The present systematic review and meta-analysis of diagnostic test accuracy
summarizes the last three decades in advances on diagnosis of Alzheimer's disease (AD) in …

Multimodal medical imaging has a larger volume of data compared to unimodal medical
imaging, and can reflect different biological information and tissue features of the human …