Author:
Tang Zhenyu,Zhang Zhenyu,Liu Huabing,Nie Dong,Yan Jing
Publisher
Springer Nature Switzerland
Reference21 articles.
1. Isensee, F., Kickingereder, P., Wick, W., Bendszus, M., Maier-Hein, K.H.: Brain tumor segmentation and radiomics survival prediction: contribution to the brats 2017 challenge. In: International MICCAI Brainlesion Workshop (2017)
2. Breiman, L.: Random forests. Mach. Learn. 45, 5–32 (2001)
3. Gillies, R.J., Kinahan, P.E., Hricak, H.: Radiomics: images are more than pictures, they are data. Radiology 278(2), 563–577 (2016)
4. Nie, D., Zhang, H., Ehsan, A., Liu, A., Shen, D.: 3D deep learning for multi-modal imaging-guided survival time prediction of brain tumor patients. In: MICCAI (2016)
5. Krizhevsky, A., Sutskever, I., Hinton, G.: ImageNet classification with deep convolutional neural networks. In: NIPS (2012)