[HTML][HTML] Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization

F Hu, AA Chen, H Horng, V Bashyam, C Davatzikos… - NeuroImage, 2023 - Elsevier
Magnetic resonance imaging and computed tomography from multiple batches (eg sites,
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …

MAGNIMS consensus recommendations on the use of brain and spinal cord atrophy measures in clinical practice

J Sastre-Garriga, D Pareto, M Battaglini… - Nature Reviews …, 2020 - nature.com
Early evaluation of treatment response and prediction of disease evolution are key issues in
the management of people with multiple sclerosis (MS). In the past 20 years, MRI has …

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

DJ Hagler Jr, SN Hatton, MD Cornejo, C Makowski… - Neuroimage, 2019 - Elsevier
Abstract The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing,
nationwide study of the effects of environmental influences on behavioral and brain …

OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and Alzheimer disease

PJ LaMontagne, TLS Benzinger, JC Morris, S Keefe… - medrxiv, 2019 - medrxiv.org
ABSTRACT OASIS-3 is a compilation of MRI and PET imaging and related clinical data for
1098 participants who were collected across several ongoing studies in the Washington …

Harmonization of cortical thickness measurements across scanners and sites

JP Fortin, N Cullen, YI Sheline, WD Taylor, I Aselcioglu… - Neuroimage, 2018 - Elsevier
With the proliferation of multi-site neuroimaging studies, there is a greater need for handling
non-biological variance introduced by differences in MRI scanners and acquisition …

Safety, efficacy, and feasibility of intranasal insulin for the treatment of mild cognitive impairment and Alzheimer disease dementia: a randomized clinical trial

S Craft, R Raman, TW Chow, MS Rafii, CK Sun… - JAMA …, 2020 - jamanetwork.com
Importance Insulin modulates aspects of brain function relevant to Alzheimer disease and
can be delivered to the brain using intranasal devices. To date, the use of intranasal insulin …

Dual attention multi-instance deep learning for Alzheimer's disease diagnosis with structural MRI

W Zhu, L Sun, J Huang, L Han… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Structural magnetic resonance imaging (sMRI) is widely used for the brain neurological
disease diagnosis, which could reflect the variations of brain. However, due to the local …

Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

JH Cole, RPK Poudel, D Tsagkrasoulis, MWA Caan… - NeuroImage, 2017 - Elsevier
Abstract Machine learning analysis of neuroimaging data can accurately predict
chronological age in healthy people. Deviations from healthy brain ageing have been …

A randomized, double-blind, placebo-controlled trial of resveratrol for Alzheimer disease

RS Turner, RG Thomas, S Craft, CH Van Dyck… - Neurology, 2015 - AAN Enterprises
Objective: A randomized, placebo-controlled, double-blind, multicenter 52-week phase 2
trial of resveratrol in individuals with mild to moderate Alzheimer disease (AD) examined its …

The minimal preprocessing pipelines for the Human Connectome Project

MF Glasser, SN Sotiropoulos, JA Wilson, TS Coalson… - Neuroimage, 2013 - Elsevier
Abstract The Human Connectome Project (HCP) faces the challenging task of bringing
multiple magnetic resonance imaging (MRI) modalities together in a common automated …