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Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference.

, , , , , and . CNI@MICCAI, volume 10511 of Lecture Notes in Computer Science, page 98-107. Springer, (2017)

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Kernel partial least squares regression for relating functional brain network topology to clinical measures of behavior., , , , , and . ISBI, page 1303-1306. IEEE, (2016)Topological Data Analysis of Functional MRI Connectivity in Time and Space Domains., , , and . CNI@MICCAI, volume 11083 of Lecture Notes in Computer Science, page 67-77. Springer, (2018)Riemannian Regression and Classification Models of Brain Networks Applied to Autism., , , and . CNI@MICCAI, volume 11083 of Lecture Notes in Computer Science, page 78-87. Springer, (2018)Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference., , , , , and . CNI@MICCAI, volume 10511 of Lecture Notes in Computer Science, page 98-107. Springer, (2017)Dynamical stability of intrinsic connectivity networks., and . NeuroImage, 59 (4): 4022-4031 (2012)Assessment of white matter microstructure in stroke patients using NODDI., , , , , and . EMBC, page 742-745. IEEE, (2014)Spatial Regularization of Functional Connectivity Using High-Dimensional Markov Random Fields., , , , and . MICCAI (2), volume 6362 of Lecture Notes in Computer Science, page 363-370. Springer, (2010)Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale., , , , , and . MICCAI (3), volume 11766 of Lecture Notes in Computer Science, page 736-744. Springer, (2019)Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance., , and . MICCAI (4), volume 11767 of Lecture Notes in Computer Science, page 102-110. Springer, (2019)Monte Carlo Expectation Maximization with Hidden Markov Models to Detect Functional Networks in Resting-State fMRI., , , , and . MLMI, volume 7009 of Lecture Notes in Computer Science, page 59-66. Springer, (2011)