This study investigates a 3D and fully convolutional neural network (CNN) for subcortical
brain structure segmentation in MRI. 3D CNN architectures have been generally avoided …

Abstract Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering
work of Rohlfing, et al.(2004), Klein, et al.(2005), and Heckemann, et al.(2006), is becoming …

For the past 25 years, the field of neuroimaging has witnessed the development of several
software packages for processing multi-parametric magnetic resonance imaging (mpMRI) to …

Background A recent meeting of international imaging experts sponsored by the
International Spinal Research Trust (ISRT) and the Wings for Life Foundation identified 5 …

Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

Gray matter (GM) tissue changes have been associated with a wide range of neurological
disorders and were recently found relevant as a biomarker for disability in amyotrophic …

An important image processing step in spinal cord magnetic resonance imaging is the ability
to reliably and accurately segment grey and white matter for tissue specific analysis. There …

Template-based analysis has proven to be an efficient, objective and reproducible way of
extracting relevant information from multi-parametric MRI data. Using common atlases, it is …

Introduction There is a need to develop imaging methods sensitive to axonal injury in
multiple sclerosis (MS), given the prominent impact of axonal pathology on disability and …

The field of spinal cord MRI is lacking a common template, as existing for the brain, which
would allow extraction of multi-parametric data (diffusion-weighted, magnetization transfer …