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Multilabel, Multiscale Topological Transformation for Cerebral MRI Segmentation Post-processing., , , , , , , and . ISMM, volume 11564 of Lecture Notes in Computer Science, page 471-482. Springer, (2019)Multiscale brain MRI super-resolution using deep 3D convolutional networks., , , , , , and . Comput. Medical Imaging Graph., (2019)Simultaneous Super-Resolution and Segmentation Using a Generative Adversarial Network: Application to Neonatal Brain MRI., , , , , , and . ISBI, page 991-994. IEEE, (2019)An iterative multi-atlas patch-based approach for cortex segmentation from neonatal MRI., , , , , and . Comput. Medical Imaging Graph., (2018)Watervoxels., , , , , , , and . Image Process. Line, (2019)Supervised quality evaluation of binary partition trees for object segmentation., , , , , , , and . Pattern Recognit., (2021)Hierarchical Approach for Neonate Cerebellum Segmentation from MRI: An Experimental Study., , , , , , , and . ISMM, volume 11564 of Lecture Notes in Computer Science, page 483-495. Springer, (2019)SegSRGAN: Super-resolution and segmentation using generative adversarial networks - Application to neonatal brain MRI., , , , , , , , , and . Comput. Biol. Medicine, (2020)Evaluation of cortical segmentation pipelines on clinical neonatal MRI data., , , , , , , and . EMBC, page 6553-6556. IEEE, (2019)