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Connectivity-Based Brain Parcellation - A Connectivity-Based Atlas for Schizophrenia Research.

, , , , , and . Neuroinformatics, 14 (1): 83-97 (2016)

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Brain tumor image segmentation using kernel dictionary learning., , , and . EMBC, page 658-661. IEEE, (2015)A Data-Driven Approach to Extract Connectivity Structures from Diffusion Tensor Imaging Data., , , and . CoRR, (2018)Dynamic network model with continuous valued nodes for longitudinal brain morphometry., , , and . NeuroImage, (2017)Network analysis of mild cognitive impairment., and . NeuroImage, 29 (4): 1252-1259 (2006)Application of a data-mining method based on Bayesian networks to lesion-deficit analysis., and . NeuroImage, 19 (4): 1664-1673 (2003)Motion correction in MRI using deep learning and a novel hybrid loss function., , , , , , , , and . CoRR, (2022)Connectivity-Based Brain Parcellation - A Connectivity-Based Atlas for Schizophrenia Research., , , , , and . Neuroinformatics, 14 (1): 83-97 (2016)Machine Learning Detects Distinct Subtypes of Minimal Cognitive Impairment., and . J. Signal Process. Syst., 94 (5): 437-443 (2022)A data-driven approach to extract connectivity structures from diffusion tensor imaging data., , , and . IEEE BigData, page 944-951. IEEE Computer Society, (2015)Scalable Algorithms for Generating and Analyzing Structural Brain Networks with a Varying Number of Nodes., , , and . CoRR, (2016)