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Bi-directional ConvLSTM U-net with densley connected convolutions
, Article 17th IEEE/CVF International Conference on Computer Vision Workshop, ICCVW 2019, 27 October 2019 through 28 October 2019 ; 2019 , Pages 406-415 ; 9781728150239 (ISBN) ; Asadi Aghbolaghi, M ; Fathy, M ; Escalera, S ; Computer Vision Foundation; IEEE ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
In recent years, deep learning-based networks have achieved state-of-the-art performance in medical image segmentation. Among the existing networks, U-Net has been successfully applied on medical image segmentation. In this paper, we propose an extension of U-Net, Bi-directional ConvLSTM U-Net with Densely connected convolutions (BCDU-Net), for medical image segmentation, in which we take full advantages of U-Net, bi-directional ConvLSTM (BConvLSTM) and the mechanism of dense convolutions. Instead of a simple concatenation in the skip connection of U-Net, we employ BConvLSTM to combine the feature maps extracted from the corresponding encoding path and the previous decoding up-convolutional...