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Automatic Segmentation of the Intracranial Volume in Fetal MR Images.

, , , , , , , , , and . FIFI/OMIA@MICCAI, volume 10554 of Lecture Notes in Computer Science, page 42-51. Springer, (2017)

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Inferring a third spatial dimension from 2D histological images., , , , and . ISBI, page 586-589. IEEE, (2018)Adversarial Training and Dilated Convolutions for Brain MRI Segmentation., , , , and . DLMIA/ML-CDS@MICCAI, volume 10553 of Lecture Notes in Computer Science, page 56-64. Springer, (2017)Supervised novelty detection in brain tissue classification with an application to white matter hyperintensities., , , , , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 978421. SPIE, (2016)Convolutional Neural Network-Based Regression for Quantification of Brain Characteristics Using MRI., , , , , , and . WorldCIST (2), volume 931 of Advances in Intelligent Systems and Computing, page 577-586. Springer, (2019)Deformable image registration using convolutional neural networks., , , , and . Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 105740S. SPIE, (2018)Automatic Segmentation of the Intracranial Volume in Fetal MR Images., , , , , , , , , and . FIFI/OMIA@MICCAI, volume 10554 of Lecture Notes in Computer Science, page 42-51. Springer, (2017)Isointense infant brain MRI segmentation with a dilated convolutional neural network., and . CoRR, (2017)Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images., , , , and . DLMIA/ML-CDS@MICCAI, volume 10553 of Lecture Notes in Computer Science, page 83-91. Springer, (2017)