scispace - formally typeset
C

Charles DeCarli

Researcher at University of California, Davis

Publications -  721
Citations -  77364

Charles DeCarli is an academic researcher from University of California, Davis. The author has contributed to research in topics: Dementia & Hyperintensity. The author has an hindex of 125, co-authored 614 publications receiving 65820 citations. Previous affiliations of Charles DeCarli include University of Southern California & French Institute of Health and Medical Research.

Papers
More filters
Journal ArticleDOI

Association of Apolipoprotein E ɛ4 Allele with Enlarged Perivascular Spaces

TL;DR: The relationship between APOE‐ɛ4 and the topography and burden of enlarged perivascular spaces is studied to elucidate underlying mechanisms between APoe‐ɚ4 and adverse clinical outcomes.
Journal ArticleDOI

Dual cognitive and mobility impairments and future dementia ‐ Setting a research agenda

TL;DR: In 2019, the National Institute on Aging Intramural and extramural Programs jointly organized a workshop on Biology Underlying Moving and Thinking to explore the hypothesis that older persons with dual decline may develop dementia through a specific pathophysiological pathway as mentioned in this paper .
Journal ArticleDOI

Association of Subjective Memory Complaints With White Matter Hyperintensities and Cognitive Decline Among Older Adults in Chicago, Illinois

TL;DR: In this article , the authors evaluated the association of subjective memory complaints (SMCs) with WMH volumes and cognitive decline and investigated the role of WMH volume in the association between SMCs and cognitive degradation.

ACCURACY OF BMAS HIPPOCAMPUS SEGMENTATION USING THE HARMONIZED HIPPOCAMPAL PROTOCOL - AAIC 2014 - Poster Session

TL;DR: Combined application of fMRI and VBM allows to assess brain atrophy along with functional component of memory impairment and can help to detect Alzheimer’s disease related changes before they may be revealed by means of conventional MRI study.
Patent

Systems and methods for measuring longitudinal brain change incorporating boundary-based analysis with tensor-based morphometry

TL;DR: In this paper, a method for computing a longitudinal change in the structure of a brain is presented. But the method requires the first image of the brain to be captured at a first time, and the second image to be taken at a second time.