Convolutional neural networks for medical image segmentation

Jeroen Bertels David Robben Robin Lemmens Processing Speech and Images Processing Speech and Images Laboratory of Neurobiology Department of Electrical Engineering Department of Electrical Engineering Department of Neurosciences KU Leuven, Belgium KU Leuven, Belgium KU Leuven, Belgium jeroen.bertels@kuleuven.be Dirk Vandermeulen Processing Speech and Images Department of Electrical Engineering KU Leuven, Belgium dirk.vandermeulen@kuleuven.be In this article, we look into some essential aspects of convolutional neural networks (CNNs) with the focus on medical image segmentation. First, we discuss the CNN architecture, thereby highlighting the spatial origin of the data, voxel-wise classification and the receptive field. Second, we discuss the sampling of input-output pairs, thereby highlighting the interaction between voxel-wise classification, patch size and the receptive field.