A deep learning approach for automated diagnosis and multi-class classification of Alzheimer's disease stages using resting-state fMRI and residual neural networks
Alzheimer's disease (AD) is an incurable neurodegenerative disorder accounting for 70%–
80% dementia cases worldwide. Although, research on AD has increased in recent years …
80% dementia cases worldwide. Although, research on AD has increased in recent years …
Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging
Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders
and a growing number of other indications are investigated in clinical trials. To ensure …
and a growing number of other indications are investigated in clinical trials. To ensure …
An improved neuroanatomical model of the default-mode network reconciles previous neuroimaging and neuropathological findings
The brain is constituted of multiple networks of functionally correlated brain areas, out of
which the default-mode network (DMN) is the largest. Most existing research into the DMN …
which the default-mode network (DMN) is the largest. Most existing research into the DMN …
3d self-supervised methods for medical imaging
Self-supervised learning methods have witnessed a recent surge of interest after proving
successful in multiple application fields. In this work, we leverage these techniques, and we …
successful in multiple application fields. In this work, we leverage these techniques, and we …
ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data
Head motion during functional MRI (fMRI) scanning can induce spurious findings and/or
harm detection of true effects. Solutions have been proposed, including deleting …
harm detection of true effects. Solutions have been proposed, including deleting …
Mechanical characterization of human brain tissue
Mechanics are increasingly recognized to play an important role in modulating brain form
and function. Computational simulations are a powerful tool to predict the mechanical …
and function. Computational simulations are a powerful tool to predict the mechanical …
[HTML][HTML] Bayesian model reduction and empirical Bayes for group (DCM) studies
This technical note describes some Bayesian procedures for the analysis of group studies
that use nonlinear models at the first (within-subject) level–eg, dynamic causal models–and …
that use nonlinear models at the first (within-subject) level–eg, dynamic causal models–and …