[HTML][HTML] Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization
Magnetic resonance imaging and computed tomography from multiple batches (eg sites,
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …
Reproducibility in neuroimaging analysis: challenges and solutions
R Botvinik-Nezer, TD Wager - Biological Psychiatry: Cognitive …, 2023 - Elsevier
Recent years have marked a renaissance in efforts to increase research reproducibility in
psychology, neuroscience, and related fields. Reproducibility is the cornerstone of a solid …
psychology, neuroscience, and related fields. Reproducibility is the cornerstone of a solid …
Style transfer generative adversarial networks to harmonize multisite MRI to a single reference image to avoid overcorrection
Recent work within neuroimaging consortia have aimed to identify reproducible, and often
subtle, brain signatures of psychiatric or neurological conditions. To allow for high‐powered …
subtle, brain signatures of psychiatric or neurological conditions. To allow for high‐powered …
[HTML][HTML] Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study
To learn multiscale functional connectivity patterns of the aging brain, we built a brain age
prediction model of functional connectivity measures at seven scales on a large fMRI …
prediction model of functional connectivity measures at seven scales on a large fMRI …
Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning
Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate,
small in effect size and have limited clinical relevance. These concerns have prompted a …
small in effect size and have limited clinical relevance. These concerns have prompted a …
[HTML][HTML] Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures
V Belov, T Erwin-Grabner, M Aghajani, A Aleman… - Scientific reports, 2024 - nature.com
Abstract Machine learning (ML) techniques have gained popularity in the neuroimaging field
due to their potential for classifying neuropsychiatric disorders. However, the diagnostic …
due to their potential for classifying neuropsychiatric disorders. However, the diagnostic …
[HTML][HTML] Elucidating salient site-specific functional connectivity features and site-invariant biomarkers in schizophrenia via deep neural networks
Schizophrenia is a highly heterogeneous disorder and salient functional connectivity (FC)
features have been observed to vary across study sites, warranting the need for methods …
features have been observed to vary across study sites, warranting the need for methods …
[HTML][HTML] Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study
Abstract The Adolescent Brain Cognitive Development (ABCD) Study® has collected data
from over 10,000 children across 21 sites, providing insights into adolescent brain …
from over 10,000 children across 21 sites, providing insights into adolescent brain …
[HTML][HTML] Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk
Y Zhu, N Maikusa, J Radua, PG Sämann… - Molecular …, 2024 - nature.com
Abstract Machine learning approaches using structural magnetic resonance imaging (sMRI)
can be informative for disease classification, although their ability to predict psychosis is …
can be informative for disease classification, although their ability to predict psychosis is …
Brain structural covariance network features are robust markers of early heavy alcohol use
Abstract Background and Aims Recently, we demonstrated that a distinct pattern of structural
covariance networks (SCN) from magnetic resonance imaging (MRI)‐derived …
covariance networks (SCN) from magnetic resonance imaging (MRI)‐derived …