[HTML][HTML] Predicting brain amyloid using multivariate morphometry statistics, sparse coding, and correntropy: validation in 1,101 individuals from the ADNI and OASIS …

J Wu, Q Dong, J Gui, J Zhang, Y Su, K Chen… - Frontiers in …, 2021 - frontiersin.org
Biomarker assisted preclinical/early detection and intervention in Alzheimer's disease (AD)
may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is …

[HTML][HTML] Diagnosis and prognosis of Alzheimer's disease using brain morphometry and white matter connectomes

Y Wang, C Xu, JH Park, S Lee, Y Stern, S Yoo… - NeuroImage: Clinical, 2019 - Elsevier
Accurate, reliable prediction of risk for Alzheimer's disease (AD) is essential for early,
disease-modifying therapeutics. Multimodal MRI, such as structural and diffusion MRI, is …

[HTML][HTML] Select Atrophied Regions in Alzheimer disease (SARA): An improved volumetric model for identifying Alzheimer disease dementia

LN Koenig, GS Day, A Salter, S Keefe, LM Marple… - NeuroImage: Clinical, 2020 - Elsevier
Abstract Introduction Volumetric biomarkers for Alzheimer disease (AD) are attractive due to
their wide availability and ease of administration, but have traditionally shown lower …

Hippocampus morphometry study on pathology-confirmed Alzheimer's disease patients with surface multivariate morphometry statistics

J Wu, J Zhang, J Shi, K Chen, RJ Caselli… - 2018 IEEE 15th …, 2018 - ieeexplore.ieee.org
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative diseases in
elderly and the incidence of this disease is increasing with older ages. One of the hallmarks …

[HTML][HTML] Federated morphometry feature selection for hippocampal morphometry associated beta-amyloid and tau pathology

J Wu, Q Dong, J Zhang, Y Su, T Wu… - Frontiers in …, 2021 - frontiersin.org
Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as
the defining hallmarks of Alzheimer's disease (AD), followed by structural atrophy detectable …

Improved prediction of imminent progression to clinically significant memory decline using surface multivariate morphometry statistics and sparse coding

CM Stonnington, J Wu, J Zhang, J Shi… - Journal of …, 2021 - content.iospress.com
Background: Besides their other roles, brain imaging and other biomarkers of Alzheimer's
disease (AD) have the potential to inform a cognitively unimpaired (CU) person's likelihood …

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images …

K Popuri, D Ma, L Wang, MF Beg - Human Brain Mapping, 2020 - Wiley Online Library
Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate
prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1 …

[HTML][HTML] Comparison of different MRI-based morphometric estimates for defining neurodegeneration across the Alzheimer's disease continuum

SL Allison, RL Koscik, RP Cary, EM Jonaitis… - NeuroImage: Clinical, 2019 - Elsevier
Background Several neurodegeneration (N) metrics using structural MRI are used for the
purpose of Alzheimer's disease (AD)-related staging, including hippocampal volume, global …

Developing univariate neurodegeneration biomarkers with low-rank and sparse subspace decomposition

G Wang, Q Dong, J Wu, Y Su, K Chen, Q Su… - Medical image …, 2021 - Elsevier
Cognitive decline due to Alzheimer's disease (AD) is closely associated with brain structure
alterations captured by structural magnetic resonance imaging (sMRI). It supports the validity …

Empowering cortical thickness measures in clinical diagnosis of Alzheimer's disease with spherical sparse coding

J Zhang, Y Fan, Q Li, PM Thompson… - 2017 IEEE 14th …, 2017 - ieeexplore.ieee.org
Cortical thickness estimation performed in vivo via magnetic resonance imaging (MRI) is an
important technique for the diagnosis and understanding of the progression of Alzheimer's …