1. Abadi M, Agarwal A, Barham P, Brevdo E, Chen Z, Citro C, Corrado GS, Davis A, Dean J, Devin M, Ghemawat S, Goodfellow I, Harp A, Irving G, Isard M, Jia Y, Jozefowicz R, Kaiser L, Kudlur M, Levenberg J, Mané D, Monga R, Moore S, Murray D, Olah C, Schuster M, Shlens J, Steiner B, Sutskever I, Talwar K, Tucker P, Vanhoucke V, Vasudevan V, Viégas F, Vinyals O, Warden P, Wattenberg M, Wicke M, Yu Y, Zheng X (2015) TensorFlow: Large-scale machine learning on heterogeneous systems.
https://www.tensorflow.org/
. Software available from tensorflow.org
2. Afshin M, Ayed IB, Punithakumar K, Law M, Islam A, Goela A, Peters T, Li S (2014) Regional assessment of cardiac left ventricular myocardial function via mri statistical features. IEEE Trans Med Imaging 33(2):481–494
3. Avola D, Cinque L (2008) Encephalic nmr image analysis by textural interpretation. In: Proceedings of the 2008 ACM symposium on applied computing, pp 1338–1342. ACM
4. Avola D, Cinque L, Di Girolamo M (2011) A novel t-cad framework to support medical image analysis and reconstruction. In: International conference on image analysis and processing, pp 414–423. Springer
5. Bernard O, Lalande A, Zotti C, Cervenansky F, Yang X, Heng PA, Cetin I, Lekadir K, Camara O, Ballester MAG et al (2018) Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: Is the problem solved? IEEE Transactions on Medical Imaging