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Convolutional neural networks for medical image segmentation

2022-11-17 14:32:01
Jeroen Bertels, David Robben, Robin Lemmens, Dirk Vandermeulen
arXiv_CV
             
Abstract

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. Finally, we give a historical overview of crucial changes to CNN architectures for classification and segmentation, giving insights in the relation between three pivotal CNN architectures: FCN, U-Net and DeepMedic.

Abstract (translated)

URL

https://arxiv.org/abs/2211.09562

PDF

https://arxiv.org/pdf/2211.09562.pdf

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