Results 91 to 100 of about 19,436 (200)

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change

NeuroImage: Clinical, 2017
Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS).
Owen A. Williams, Eva A. Zeestraten, Philip Benjamin, Christian Lambert, Andrew J. Lawrence, Andrew D. Mackinnon, Robin G. Morris, Hugh S. Markus, Rebecca A. Charlton, Thomas R. Barrick   +9 more
doaj   +1 more source

Plasma and neuroimaging biomarkers of small vessel disease and Alzheimer's disease in a diverse cohort: MESA

Alzheimer's &Dementia, Volume 22, Issue 2, February 2026.
Abstract INTRODUCTION Little is known about how Alzheimer's disease (AD) plasma biomarkers relate to cerebral small vessel disease (cSVD) neuroimaging biomarkers. METHODS The study involved 251 Wake Forest Multi‐Ethnic Study of Atherosclerosis (MESA) Exam 6 participants with plasma AD biomarkers, magnetic resonance imaging, amyloid positron emission ...
Samuel N. Lockhart, Courtney L. Sutphen, Jordan Tanley, Fernando Gonzalez‐Ortiz, Przemysław R. Kac, Mohamad Habes, Susan R. Heckbert, Nicholas J. Ashton, Michelle M. Mielke, Robert Koeppe, Marc D. Rudolph, Kiran K. Solingapuram Sai, Christopher T. Whitlow, Kevin D. Hiatt, Suzanne Craft, Thomas C. Register, Kathleen M. Hayden, Stephen R. Rapp, Bonnie C. Sachs, Henrik Zetterberg, Kaj Blennow, Thomas K. Karikari, Timothy M. Hughes   +22 more
wiley   +1 more source

Resolving cognitive heterogeneity in white matter hyperintensities through integrated analyses of microbiome, metabolome, and brain glymphatic function

Alzheimer's &Dementia, Volume 22, Issue 2, February 2026.
Abstract INTRODUCTION Individuals with similar white matter hyperintensities (WMH) burden show heterogeneous cognitive outcomes, yet the biological mechanisms underlying this variability remain incompletely understood. METHODS We integrated 16S rDNA sequencing, untargeted metabolomics, and multi‐modal magnetic resonance imaging (MRI) to comprehensively
Xiaotao Xu, Xia Zhou, Mengwei Zhang, Jingjing Fang, Zhiqing Yan, Xiaoqun Zhu, Yongqiang Yu, Jiajia Zhu   +7 more
wiley   +1 more source

A mixed EIM-SVD tensor decomposition for bivariate functions

, 2017
In this paper we present a mixed EIM-SVD tensor decomposition for bivariate functions. This method is composed, as its name suggests, of two main steps. The first one, provides an approximate representation of a function $f$ in separate form by the use of a Tensor Empirical Interpolation Method (TEIM). The second phase consists in applying the Singular
De Vuyst, Florian, Toumi, Asma
openaire   +2 more sources

Vascular smooth muscle cell loss, but not neuroinflammation, drives cerebrovascular reactivity impairment in Alzheimer's disease

Alzheimer's &Dementia, Volume 22, Issue 2, February 2026.
Abstract INTRODUCTION Cerebrovascular reactivity (CVR) impairment is a key feature of Alzheimer's disease and related dementias (ADRD), but its mechanistic basis remains unclear. This study examined whether vascular smooth muscle cell (VSMC) loss, rather than amyloidosis or neuroinflammation, underlies CVR deficits.
Xiuli Yang, Yuguo Li, Minmin Yao, Adnan Bibic, Wenzhen Duan, Hanzhang Lu, Zhiliang Wei   +6 more
wiley   +1 more source

A Tensor-Based Subspace Approach for Bistatic MIMO Radar in Spatial Colored Noise

Sensors, 2014
In this paper, a new tensor-based subspace approach is proposed to estimate the direction of departure (DOD) and the direction of arrival (DOA) for bistatic multiple-input multiple-output (MIMO) radar in the presence of spatial colored noise.
Xianpeng Wang, Wei Wang, Xin Li, Junxiang Wang   +3 more
doaj   +1 more source

Multishot Compressive Hyperspectral Imaging Based on Tensor Fibered Rank Minimization and Its Primal-Dual Algorithm

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Coded aperture snapshot spectral imaging (CASSI) compresses tens to hundreds of spectral bands of the hyperspectral image (HSI) to a 2-D compressive measurement.
Ting Xie, Xudong Kang, Renwei Dian, Tonghan Wang, Licheng Liu   +4 more
doaj   +1 more source

Tensor Decompositions via Two-Mode Higher-Order SVD (HOSVD)

, 2016
Tensor decompositions have rich applications in statistics and machine learning, and developing efficient, accurate algorithms for the problem has received much attention recently. Here, we present a new method built on Kruskal's uniqueness theorem to decompose symmetric, nearly orthogonally decomposable tensors.
Wang, Miaoyan, Song, Yun S.
openaire   +2 more sources

MULTILINEAR SINGULAR VALUE DECOMPOSITION FOR STRUCTURED TENSORS

, 2008
International audienceThe Higher-Order SVD (HOSVD) is a generalization of the Singular Value Decompo- sition (SVD) to higher-order tensors (i.e. arrays with more than two indices) and plays an important role in various domains.
Badeau, Roland, Boyer, Remy
core   +1 more source

An optimization approach for dynamical Tucker tensor approximation

Results in Applied Mathematics, 2019
An optimization-based approach for Tucker tensor approximation of parameter-dependent data tensors and solutions of tensor differential equations with low Tucker rank is presented.
Lukas Exl
doaj   +1 more source