ResCap: Residual Capsules Network for Medical Image Segmentation

Authors
Nguyen, Chanh D.Tr.
Dao, Huu-Hung
Huynh, Minh-Thanh
Phu Ward, Tan

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
Convolutional neural networks (CNNs) have shown remarkable results for a wide range of task in computer vision. However, CNNs has the limitation of poor translation invariance and lack of information about pose; thus, it requires a lot of data. Capsule networks, however, have the ability to preserve information about the pose. In this paper, we present a capsule-based network for medical image segmentation. We adopt the contracting path of the U-Net architecture. The network achieves the same accuracy as U-Net but is much smaller (0.16% number of parameters compared with U-Net).

Identifiers
doi: 10.24926/548719.058