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Recent findings raised evidence that in early-onset left temporal lobe epilepsy, women show greater functional plasticity for verbal memory than men. In particular, women with lesion- or epilepsy-driven atypical language dominance show an advantage over men. The question asked in this study was whether there is evidence of sex- and language(More)
A new automatic method for multiple sclerosis (MS) lesion segmentation in multi-channel 3D MR images is presented. The main novelty of the method is that it learns the spatial image features needed for training a supervised classifier entirely from unlabeled data. This is in contrast to other current supervised methods, which typically require the user to(More)
Deep learning has traditionally been computationally expensive, and advances in training methods have been the prerequisite for improving its efficiency in order to expand its application to a variety of image classification problems. In this letter, we address the problem of efficient training of convolutional deep belief networks by learning the weights(More)
Changes in brain morphology and white matter lesions are two hallmarks of multiple sclerosis (MS) pathology, but their variability beyond volumetrics is poorly characterized. To further our understanding of complex MS pathology, we aim to build a statistical model of brain images that can automatically discover spatial patterns of variability in brain(More)
Recent ®ndings raised evidence that in early-onset left temporal lobe epilepsy, women show greater functional plasticity for verbal memory than men. In particular, women with lesion-or epilepsy-driven atypical language dominance show an advantage over men. The question asked in this study was whether there is evidence of sex-and language dominance-dependent(More)
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