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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Shallow Fully-Connected Neural Networks for Ischemic Stroke-Lesion Segmentation in MRI
verfasst von : Christian Lucas, Oskar Maier, Mattias P. Heinrich
Erschienen in: Bildverarbeitung für die Medizin 2017
Verlag: Springer Berlin Heidelberg
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Automatic image segmentation of stroke lesions could be of great importance for aiding the treatment decision. Convolutional neural networks obtain high accuracy for this task at the cost of prohibitive computational demand for time-sensitive clinical scenarios. In this work, we study the use of classical fully-connected neural networks (FC-NN) based on hand-crafted features, which achieve much shorter runtimes. We show that recent advances in optimization and regularization of deep learning can be successfully transferred to FC-NNs to improve the training process and achieve comparable accuracy to random decision forests.