The semantic image segmentation task consists of classifying each pixel of an image into an
instance, where each instance corresponds to a class. This task is a part of the concept of …

Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments
restores walking in people with spinal cord injury (SCI). However, EES is delivered with …

Recent advances in deep learning methods have redefined the state-of-the-art for many
medical imaging applications, surpassing previous approaches and sometimes even …

Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges,
including a lack of standardized imaging protocols. Here we present a prospectively …

In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI
protocol that provides valuable metrics for assessing spinal cord macrostructural and …

This review paper provides a detailed evaluation of the existing landscape and future trends
in applying machine learning and deep learning approaches for predicting concrete strength …

Deep learning (DL) models in general and convolutional neural networks (CNN) in
particular, have rapidly turned out to be methodologies of interest for applications concerned …

The spinal cord is frequently affected in multiple sclerosis (MS), causing motor, sensory and
autonomic dysfunction. A number of pathological abnormalities, including demyelination …

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for
multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had …