Over the last few decades, the improved diagnostic criteria, the wide use of MRI, and the
growing availability of effective pharmacologic treatments have led to substantial advances …

Introduction: Over the past few years, the deep learning community has developed and
validated a plethora of tools for lesion detection and segmentation in Multiple Sclerosis …

Arterial spin labeling (ASL) has undergone significant development since its inception, with
a focus on improving standardization and reproducibility of its acquisition and quantification …

Objective: To investigate the performance of deep learning (DL) based on fully convolutional
neural network (FCNN) in segmenting brain tissues in a large cohort of multiple sclerosis …

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel
disease, that is increasingly studied with large, pooled multicenter datasets. This data …

Brain vascular damage accumulate in aging and often manifest as white matter
hyperintensities (WMHs) on MRI. Despite increased interest in automated methods to …

In this work we present BIANCA‐MS, a novel tool for brain white matter lesion segmentation
in multiple sclerosis (MS), able to generalize across both the wide spectrum of MRI …

Frontal lobe structures decline faster than most other brain regions in older adults. Age-
related change in the frontal lobe is associated with poorer executive function (eg, working …

Objectives Medical image analysis practices face challenges that can potentially be
addressed with algorithm-based segmentation tools. In this study, we map the field of …

White matter lesions (WML) in the brain are thought to be related to ischemic processes,
demyelination, and axonal degeneration. The presence of WML predict cognitive decline …