μ-Net: Medical image segmentation using efficient and effective deep supervision
Author:
Publisher
Elsevier BV
Subject
Health Informatics,Computer Science Applications
Reference52 articles.
1. NiftyNet: A deep-learning platform for medical imaging;Gibson;Comput. Methods Programs Biomed.,2018
2. Deep learning for image-based cancer detection and diagnosis: A survey;Hu;Pattern Recognit.,2018
3. A.V. Dalca, J. Guttag, M.R. Sabuncu, Anatomical priors in convolutional networks for unsupervised biomedical segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 9290–9299.
4. O. Ronneberger, P. Fischer, T. Brox, U-Net: Convolutional networks for biomedical image segmentation, in: Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, 2015, pp. 234–241.
5. M. Drozdzal, E. Vorontsov, G. Chartrand, S. Kadoury, C. Pal, The importance of skip connections in biomedical image segmentation, in: Proceedings of the International Workshop on Deep Learning in Medical Image Analysis, International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2016, pp. 179–187.
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