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Utilizing multi-modal neuroimaging data has been proved to be effective to investigate human cognitive activities and certain pathologies.
Breaking the dilemma of medical image-to-image translation
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Gs-wgan: A gradient-sanitized approach for learning differentially private generators
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A generalized framework of feature learning enhanced convolutional neural network for pathology-image-oriented cancer diagnosis
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Aggn: Attention-based glioma grading network with multi-scale feature extraction and multi-modal information fusion
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A combined manifold learning analysis of shape and appearance to characterize neonatal brain development
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