Fully Automated Pancreas Segmentation with Two-Stage 3D Convolutional Neural Networks

Author:

Zhao Ningning,Tong Nuo,Ruan Dan,Sheng Ke

Publisher

Springer International Publishing

Reference10 articles.

1. Farag, A., Lu, L., Roth, H.R., Liu, J., Turkbey, E., Summers, R.M.: A bottom-up approach for pancreas segmentation using cascaded superpixels and (deep) image patch labeling. IEEE Trans. Med. Imaging 26(1), 386–399 (2017)

2. Li, J., Lin, X., Che, H., Li, H., Qian, X.: Probability map guided bi-directional recurrent UNet for pancreas segmentation. Arxiv (2019), https://arxiv.org/abs/1903.00923

3. Oktay, O., et al.: Attention u-net: learning where to look for the pancreas. In: Medical Imaging with Deep Learning (MIDL) (2018)

4. Roth, H., et al.: Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation. Med. Image Anal. 45, 94–107 (2017)

5. Lecture Notes in Computer Science;HR Roth,2015

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