367 citations · 696 across the 18 of their papers we have counts for
3 papers · 1 filter
Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data
Abhijit Guha Roy, Sailesh Conjeti, Debdoot Sheet +3
Training deep fully convolutional neural networks (F-CNNs) for semantic image segmentation requires access to abundant labeled data. While large datasets of unlabeled image data ar…
A Multi-Armed Bandit to Smartly Select a Training Set from Big Medical Data
Benjamín Gutiérrez, Loïc Peter, Tassilo Klein +1
With the availability of big medical image data, the selection of an adequate training set is becoming more important to address the heterogeneity of different datasets. Simply inc…
DeepNAT: Deep Convolutional Neural Network for Segmenting Neuroanatomy
Christian Wachinger, Martin Reuter, Tassilo Klein
We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learn…