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Segmentation of grey matter in magnetic resonance images of the spinal cord is an important step in assessing disease state in neurological disorders such as multiple sclerosis. However, manual delineation of spinal cord tissue is time-consuming and susceptible to variability introduced by the rater. We present a novel segmentation method for spinal cord tissue that uses fully convolutional encode
