[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 …
Comparison of traveling‐subject and ComBat harmonization methods for assessing structural brain characteristics
N Maikusa, Y Zhu, A Uematsu… - Human brain …, 2021 - Wiley Online Library
Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and
development. Measurement biases—caused by site differences in scanner/image …
development. Measurement biases—caused by site differences in scanner/image …
Basal forebrain volume reliably predicts the cortical spread of Alzheimer's degeneration
Alzheimer's disease neurodegeneration is thought to spread across anatomically and
functionally connected brain regions. However, the precise sequence of spread remains …
functionally connected brain regions. However, the precise sequence of spread remains …
Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images …
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 …
prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1 …
Differential diagnosis of frontotemporal dementia, Alzheimer's disease, and Normal aging using a multi-scale multi-type feature generative adversarial deep neural …
Methods: Alzheimer's disease and Frontotemporal dementia are the first and third most
common forms of dementia. Due to their similar clinical symptoms, they are easily …
common forms of dementia. Due to their similar clinical symptoms, they are easily …
Predicting time-to-conversion for dementia of Alzheimer's type using multi-modal deep survival analysis
Abstract Dementia of Alzheimer's Type (DAT) is a complex disorder influenced by numerous
factors, and it is difficult to predict individual progression trajectory from normal or mildly …
factors, and it is difficult to predict individual progression trajectory from normal or mildly …
A comparison of intracranial volume estimation methods and their cross‐sectional and longitudinal associations with age
S Nerland, TS Stokkan, KN Jørgensen… - Human Brain …, 2022 - Wiley Online Library
Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI)
studies, both as a covariate and as a variable of interest. Findings of associations between …
studies, both as a covariate and as a variable of interest. Findings of associations between …
Construction of MRI-based Alzheimer's disease score based on efficient 3D convolutional neural network: Comprehensive validation on 7,902 images from a multi …
Background: In recent years, many convolutional neural networks (CNN) have been
proposed for the classification of Alzheimer's disease. Due to memory constraints, many of …
proposed for the classification of Alzheimer's disease. Due to memory constraints, many of …
Machine learning based multimodal neuroimaging genomics dementia score for predicting future conversion to alzheimer's disease
Background: The increasing availability of databases containing both magnetic resonance
imaging (MRI) and genetic data allows researchers to utilize multimodal data to better …
imaging (MRI) and genetic data allows researchers to utilize multimodal data to better …
Mild Motor Signs in Healthy Aging Are Associated with Lower Synaptic Density in the Brain
MGA Van Cauwenberge, A Delva… - Movement …, 2023 - Wiley Online Library
Objective To investigate whether mild motor signs (MMS) in old age correlate with synaptic
density in the brain. Background Normal aging is associated with a decline in movement …
density in the brain. Background Normal aging is associated with a decline in movement …