In this review, we discuss recent work by the ENIGMA Consortium (http://enigma. ini. usc.
edu)–a global alliance of over 500 scientists spread across 200 institutions in 35 countries …

Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and
consistency in dementia diagnosis through the use of quantitative volumetric reporting tools …

Deep-learning methods for auto-segmenting brain images either segment one slice of the
image (2D), five consecutive slices of the image (2.5 D), or an entire volume of the image …

Purpose MRI is integral to the diagnosis of multiple sclerosis (MS) and is important for
clinical prognostication. Quantitative volumetric reporting tools (QReports) can improve the …

Abstract Objective COVID-19 (SARS-CoV-2) has been associated with neurological
sequelae even in those patients with mild respiratory symptoms. Patients experiencing …

Brain areas within the motor system interact directly or indirectly during motor-imagery and
motor-execution tasks. These interactions and their functionality can change following stroke …

Purpose After radiation therapy (RT) to the brain, patients often experience memory
impairment, which may be partially mediated by damage to the hippocampus. Hippocampal …

Amyloid-β (Aβ) is ubiquitous in the central nervous system (CNS), but pathologic
accumulation of Aβ results in four distinct neurologic disorders that affect middle-aged and …

BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning
automatic brain segmentation and classification method, based on T1-weighted brain MR …

Automatic neuroimaging processing tools provide convenient and systematic methods for
extracting features from brain magnetic resonance imaging scans. One tool, FreeSurfer …