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Brain magnetic resonance (MR) images are significant for brain studies because of their excellent contrast of soft tissues, non invasive characteristic and a high spatial resolution. However, Intensity inhomogeneity is an undesired phenomenon that represents the main obstacle for brain MR image segmentation. In this paper, we propose a novel model which can overcome the intensity inhomogeneity problem...
Hidden Markov models can be used to combine behavioral and brain-imaging data from an intelligent tutoring system to track mental states during student's problem-solving episodes.
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