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Non-parametric Density Modeling and Outlier-Detection in Medical Imaging Datasets.

, , , and . MLMI, volume 7588 of Lecture Notes in Computer Science, page 210-217. Springer, (2012)

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Randomized parcellation based inference., , , , , , , , , and 10 other author(s). NeuroImage, (2014)Robust regression for large-scale neuroimaging studies., , , , , , , , , and 11 other author(s). NeuroImage, (2015)Enhancing the Reproducibility of Group Analysis with Randomized Brain Parcellations., , , , , and . MICCAI (2), volume 8150 of Lecture Notes in Computer Science, page 591-598. Springer, (2013)High-dimensional statistical methods for inter-subject studies in neuroimaging. (Analyse statistique de données en grande dimension : application à l'étude de la variabilité inter-individuelle en neuroimagerie).. University of Paris-Sud, Orsay, France, (2013)An empirical comparison of surface-based and volume-based group studies in neuroimaging., , , and . NeuroImage, 63 (3): 1443-1453 (2012)Detecting outliers in high-dimensional neuroimaging datasets with robust covariance estimators., , , , and . Medical Image Analysis, 16 (7): 1359-1370 (2012)Robust Group-Level Inference in Neuroimaging Genetic Studies., , , , , , and . PRNI, page 21-24. IEEE, (2013)Detecting Outlying Subjects in High-Dimensional Neuroimaging Datasets with Regularized Minimum Covariance Determinant., , , , and . MICCAI (3), volume 6893 of Lecture Notes in Computer Science, page 264-271. Springer, (2011)Non-parametric Density Modeling and Outlier-Detection in Medical Imaging Datasets., , , and . MLMI, volume 7588 of Lecture Notes in Computer Science, page 210-217. Springer, (2012)