31 citations · 95 across the 12 of their papers we have counts for
4 papers · 1 filter
Isointense infant brain MRI segmentation with a dilated convolutional neural network
Pim Moeskops, Josien P. W. Pluim
Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplan…
Automatic segmentation of the intracranialvolume in fetal MR images
N. Khalili, P. Moeskops, N. H. P. Claessens +7
MR images of the fetus allow non-invasive analysis of the fetal brain. Quantitative analysis of fetal brain development requires automatic brain tissue segmentation that is typical…
Adversarial training and dilated convolutions for brain MRI segmentation
Pim Moeskops, Mitko Veta, Maxime W. Lafarge +2
Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversa…
Exploring the similarity of medical imaging classification problems
Veronika Cheplygina, Pim Moeskops, Mitko Veta +2
Supervised learning is ubiquitous in medical image analysis. In this paper we consider the problem of meta-learning -- predicting which methods will perform well in an unseen class…