1. Avants BB, Tustison N, Song G (2009) Advanced normalization tools (ants). Insight J 2(365):1–35
2. Bakas S, Akbari H, Sotiras A, Bilello M, Rozycki M, Kirby JS, Freymann JB, Farahani K, Davatzikos C (2017) Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features. Sci Data 4:170117
3. Bakas S, Reyes M, Jakab A, Bauer S, Rempfler M, Crimi A, Shinohara RT, Berger C, Ha SM, Rozycki M, et al. (2018) Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge. arXiv:1811.02629
4. Brownlee J (2018) A gentle introduction to early stopping to avoid overtraining neural networks. https://machinelearningmastery.com/early-stopping-to-avoid-overtraining-neural-network-models/. [Online; accessed March 02, 2020]
5. Chen C, Liu X, Ding M, Zheng J, Li J (2019) 3d dilated multi-fiber network for real-time brain tumor segmentation in mri. In: International conference on medical image computing and computer-assisted intervention. Springer, Berlin, pp 184–192