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Using a Maximum Uncertainty LDA-Based Approach to Classify and Analyse MR Brain Images., , , , , , , и . MICCAI (1), том 3216 из Lecture Notes in Computer Science, стр. 291-300. Springer, (2004)Generalising Deep Learning MRI Reconstruction across Different Domains., , , , , , , и . CoRR, (2019)Non-linear Registration with the Variable Viscosity Fluid Algorithm., , , , , и . IPMI, том 1613 из Lecture Notes in Computer Science, стр. 238-251. Springer, (1999)Interpolation Artefacts in Non-rigid Registration., , , и . MICCAI (2), том 3750 из Lecture Notes in Computer Science, стр. 247-254. Springer, (2005)Classifier Selection Strategies for Label Fusion Using Large Atlas Databases., , , , и . MICCAI (1), том 4791 из Lecture Notes in Computer Science, стр. 523-531. Springer, (2007)A multivariate statistical analysis of the developing human brain in preterm infants., , , , , , , , и . Image Vis. Comput., 25 (6): 981-994 (2007)Reconstruction of fetal brain MRI with intensity matching and complete outlier removal., , , , и . Medical Image Anal., 16 (8): 1550-1564 (2012)The effect of preterm birth on neonatal cerebral vasculature studied with magnetic resonance angiography at 3 Tesla., , , , , , , и . NeuroImage, 32 (3): 1050-1059 (2006)Normalisation of Neonatal Brain Network Measures Using Stochastic Approaches., , , , , , и . MICCAI (1), том 8149 из Lecture Notes in Computer Science, стр. 574-581. Springer, (2013)An Evaluation of Deformation-Based Morphometry Applied to the Developing Human Brain and Detection of Volumetric Changes Associated with Preterm Birth., , , , , , , , и . MICCAI (1), том 2878 из Lecture Notes in Computer Science, стр. 697-704. Springer, (2003)