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Population learning of structural connectivity by white matter encoding and decoding.

, , , , , , and . ISBI, page 554-558. IEEE, (2016)

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Classifying Phenotypes Based on the Community Structure of Human Brain Networks., , , , , , , and . GRAIL/MFCA/MICGen@MICCAI, volume 10551 of Lecture Notes in Computer Science, page 3-11. Springer, (2017)The heritability of the functional connectome is robust to common nonlinear registration methods., , , , , , , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97841R. SPIE, (2016)Age differences in specific neural connections within the Default Mode Network underlie theory of mind., , , , , and . NeuroImage, (2019)Continuous representations of brain connectivity using spatial point processes., , , , and . Medical Image Analysis, (2017)A comparison of network definitions for detecting sex differences in brain connectivity using Support Vector Machines., , , , , , , , , and . ISBI, page 961-965. IEEE, (2017)Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins., , , , , , , , , and . ISBI, page 1167-1171. IEEE, (2015)Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification., , , , , , , and . MICCAI (1), volume 10433 of Lecture Notes in Computer Science, page 515-522. Springer, (2017)Population learning of structural connectivity by white matter encoding and decoding., , , , , , and . ISBI, page 554-558. IEEE, (2016)Heritability and reliability of automatically segmented human hippocampal formation subregions., , , , , , , , , and 9 other author(s). NeuroImage, (2016)A Continuous Model of Cortical Connectivity., , , , and . MICCAI (1), volume 9900 of Lecture Notes in Computer Science, page 157-165. (2016)