Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …

The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …

In magnetic resonance (MR) imaging, a lack of standardization in acquisition often causes
pulse sequence-based contrast variations in MR images from site to site, which impedes …

In the past, the cerebellum has been best known for its crucial role in motor function.
However, increasingly more findings highlight the importance of cerebellar contributions in …

Quantifying the volume of the cerebellum and its lobes is of profound interest in various
neurodegenerative and acquired diseases. Especially for the most common spinocerebellar …

Objective The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis
(ALS) by comparing patterns of neurodegeneration using brain magnetic resonance …

The organization of the basic tissue and functional properties of the cerebellum across
development is unknown. Combining several large datasets, we demonstrate in the human …

Childhood psychiatric symptoms are often diffuse but can coalesce into discrete mental
illnesses during late adolescence. We leveraged polygenic scores (PGSs) to parse genomic …

Background Increasing evidence points to a pathophysiological role for the cerebellum in
Parkinson's disease (PD). However, regional cerebellar changes associated with motor and …

Background: The noninvasive study of the structure and functions of the brain using
neuroimaging techniques is increasingly being used for its clinical and research …