E. H. Adelson, C. H. Anderson, J. R. Bergen, P. J. Burt, and J. M. Ogden, Pyramid methods in image processing, RCA engineer, vol.29, issue.6, pp.33-41, 1984.

A. , V. Safwan, M. Krishnamurthi, and G. , Brain tumor segmentation from multi modal mr images using fully convolutional neural network, Medical Image Computing and Computer Assisted Intervention -MICCAI 2017 -20th International Conference Proceedings, pp.1-8, 2017.

S. Bakas, H. Akbari, A. Sotiras, M. Bilello, M. Rozycki et al., Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features, Scientific data, vol.4, p.170117, 2017.

C. Balasubramanian, S. Saravanan, K. Srinivasagan, and K. Duraiswamy, Automatic segmentation of brain tumor from mr image using region growing technique, Life Science Journal, vol.10, issue.2, 2013.

L. C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille, Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, IEEE transactions on pattern analysis and machine intelligence, vol.40, pp.834-848, 2018.

R. Girshick, J. Donahue, T. Darrell, and J. Malik, Rich feature hierarchies for accurate object detection and semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.580-587, 2014.

G. Huang, Z. Liu, K. Q. Weinberger, and L. Van-der-maaten, Densely connected convolutional networks, Proceedings of the IEEE conference on computer vision and pattern recognition, vol.1, p.3, 2017.

S. Ioffe and C. Szegedy, Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015.

G. Kim, Brain tumor segmentation using deep u-net, Medical Image Computing and Computer Assisted Intervention -MICCAI 2017 -20th International Conference Proceedings, pp.154-160, 2017.

M. Kistler, S. Bonaretti, M. Pfahrer, R. Niklaus, and P. Büchler, The virtual skeleton database: An open access repository for biomedical research and collaboration, J Med Internet Res, vol.15, issue.11, p.245, 2013.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012.

M. Lenvine and S. Shaheen, A modular computer vision system for image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.540-557, 1981.

T. Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan et al., Feature pyramid networks for object detection, CVPR, vol.1, p.4, 2017.

J. Long, E. Shelhamer, and T. Darrell, Fully convolutional networks for semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.3431-3440, 2015.

B. H. Menze, A. Jakab, S. Bauer, J. Kalpathy-cramer, K. Farahani et al., The multimodal brain tumor image segmentation benchmark (brats), IEEE transactions on medical imaging, vol.34, issue.10, pp.1993-2024, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00935640

S. Pereira, A. Pinto, V. Alves, and C. A. Silva, Brain tumor segmentation using convolutional neural networks in mri images, IEEE transactions on medical imaging, vol.35, issue.5, pp.1240-1251, 2016.

R. Rana, H. Bhdauria, and A. Singh, Brain tumour extraction from mri images using bounding-box with level set method, Contemporary Computing (IC3), 2013.

, Sixth International Conference on, pp.319-324, 2013.

O. Ronneberger, P. Fischer, and T. Brox, U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer-assisted intervention, pp.234-241, 2015.

R. Saha, A. Phophalia, and S. K. Mitra, Brain tumor segmentation from multimodal mr images using rough sets, International Conference on Computer Vision, Graphics, and Image processing, pp.133-144, 2016.

J. Selvakumar, A. Lakshmi, and T. Arivoli, Brain tumor segmentation and its area calculation in brain mr images using k-mean clustering and fuzzy c-mean algorithm, Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on, pp.186-190, 2012.

M. Shaikh, G. Anand, G. Acharya, A. Amrutkar, V. Alex et al., Brain tumor segmentation using dense fully convolutional neural network. In: International MICCAI Brainlesion Workshop, pp.309-319, 2017.

H. Shen, J. Zhang, and W. Zheng, Efficient symmetry-driven fully convolutional network for multimodal brain tumor segmentation, ICIP, 2017.

M. Soltaninejad, L. Zhang, T. Lambrou, N. Allinson, and X. Ye, Multimodal mri brain tumor segmentation using random forests with features learned from fully convolutional neural network, 2017.