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 …

Background: MR imaging of the spinal cord (SC) gray matter (GM) at the cervical and lumbar
enlargements' level may be particularly informative in lower motor neuron disorders, eg …

The small butterfly shaped structure of spinal cord (SC) gray matter (GM) is challenging to
image and to delineate from its surrounding white matter (WM). Segmenting GM is up to a …

Robustness is a significant constraint in machine learning models. The performance of the
algorithms must not deteriorate when training and testing with slightly different data. Deep …

BACKGROUND AND PURPOSE: Fully automatic quantification methods of spinal cord
compartments are needed to study pathologic changes of the spinal cord GM and WM in MS …

Deep neural networks models have achieved state-of-the-art results in a great number of
different tasks in different domains (eg, natural language processing and computer vision) …

Medical image segmentation is an essential part of a many healthcare services. While it is
possible for an expert to manually label each pixel or voxel in an image, it is a time …

The human spinal cord, part of the Central Nervous System (CNS), is the main pathway
responsible for the connection of brain and peripheral nervous system. The gray matter …

Network architectures and training strategies are crucial considerations in applying deep
learning to neuroimaging data, but attaining optimal performance still remains challenging …

Robustness is a significant constraint in machine learning models. The performance of the
algorithms must not deteriorate when training and testing with slightly different data. Deep …