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
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Journal ArticleDOI
Longitudinal changes in lateral ventricular volume in patients with dementia of the Alzheimer type.
Charles DeCarli,James V. Haxby,J. A. Gillette,Diane Teichberg,S. I. Rapoport,Mark B. Schapiro +5 more
TL;DR: The rate of total lateral ventricular enlargement accompanying DAT is due to continuous, pathologic cell loss, significantly greater than cell loss due to the healthy aging process.
Journal ArticleDOI
Biological heterogeneity in ADNI amnestic mild cognitive impairment.
TL;DR: This work hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications, and examined normal controls from the Alzheimer's Disease Neuroimaging Initiative for this purpose.
Journal ArticleDOI
Female sex, early-onset hypertension, and risk of dementia.
Paola Gilsanz,Elizabeth Rose Mayeda,M. Maria Glymour,Charles P. Quesenberry,Dan M Mungas,Charles DeCarli,Alexander Dean,Rachel A. Whitmer +7 more
TL;DR: Though midlife hypertension was more common in men, it was only associated with dementia risk in women, and sex differences in the timing of dementia risk factors have important implications for brain health and hypertension management.
Journal ArticleDOI
Impact of Apolipoprotein E ε4 and Vascular Disease on Brain Morphology in Men From the NHLBI Twin Study
TL;DR: This longitudinal study of the effects of cardiovascular disease risk factors in community-dwelling male veterans examined the combined effect of ApoE4 and history of vascular disease on brain volume, WMH, and MRI evidence of stroke.
Book ChapterDOI
Fully-Automated White Matter Hyperintensity Detection with Anatomical Prior Knowledge and without FLAIR
TL;DR: The method is shown to accurately detect WMHs in a set of 114 elderly subjects from an academic dementia clinic and shows that standard off-the-shelf MRF training and inference methods provide robust results, and that increasing the complexity of neighborhood dependency models does not necessarily help performance.