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Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation

  • Richard McKinleyEmail author
  • Raphael Meier
  • Roland Wiest
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11384)

Abstract

We introduce a new family of classifiers based on our previous DeepSCAN architecture, in which densely connected blocks of dilated convolutions are embedded in a shallow U-net-style structure of down/upsampling and skip connections. These networks are trained using a newly designed loss function which models label noise and uncertainty. We present results on the testing dataset of the Multimodal Brain Tumor Segmentation Challenge 2018.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Support Centre for Advanced Neuroimaging, University Institute of Diagnostic and Interventional NeuroradiologyInselspital, Bern University HospitalBernSwitzerland

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