Data-efficient Convolutional Neural Networks for Treatment Decision Support in Acute Ischemic Stroke

Apr 11, 2018 MIDL 2018 Abstract Submission readers: everyone
  • Abstract: A data-efficient Deep Learning method is presented to explore outcome prediction in Ischemic Stroke using full-sized 2D CT images. We show promising results on 3 different prediction tasks with equal or higher performance than conventional CNNs while reducing model-parameters and overfitting on limited data sets.
  • Keywords: ischemic stroke, cnn, structured receptive fields, steerable gaussians
  • Author Affiliation: Adam Hilbert, Bastiaan Veeling - University of Amsterdam, Henk Marquering - Department of Biomedical Engineering and Physics, Academical Medical Center, Amsterdam
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