Brain mri: tumor evaluation, Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, vol.24, issue.4, pp.709-724, 2006. ,
Computer aided system for brain tumor detection and segmentation, Computer Networks and Information Technology (ICCNIT), 2011 International Conference on, pp.299-302, 2011. ,
Review of mri-based brain tumor image segmentation using deep learning methods, Procedia Computer Science, vol.102, pp.317-324, 2016. ,
Gradientbased learning applied to document recognition, Proceedings of the IEEE, vol.86, issue.11, pp.2278-2324, 1998. ,
Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012. ,
Brain tumor segmentation with deep neural networks, Proceedings of the MICCAI Workshop on Multimodal Brain Tumor Segmentation Challenge BRATS, pp.1-05, 2014. ,
Deep convolutional neural networks for the segmentation of gliomas in multi-sequence mri, Proceedings of the MICCAI Workshop on Multimodal Brain Tumor Segmentation Challenge BRATS, pp.52-55, 2015. ,
Fully convolutional neural networks with hyperlocal features for brain tumor segmentation, Proceedings MICCAI-BRATS Workshop, pp.4-9, 2016. ,
Mohamed Akil, and Rostom Kachouri. Fully automatic brain tumor segmentation using end-to-end incremental deep neural networks in mri images. Computer methods and programs in biomedicine, vol.166, pp.39-49, 2018. ,
A deep learning model integrating fcnns and crfs for brain tumor segmentation, Medical image analysis, vol.43, pp.98-111, 2018. ,
Brain tumor segmentation with deep neural networks, Medical image analysis, vol.35, pp.18-31, 2017. ,
The Multi-modal Brain Tumor Image Segmentation Benchmark (BRATS), IEEE Transactions on Medical Imaging, vol.34, issue.10, pp.1993-2024, 2015. ,
Advancing The Can-cer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features, Nature Scientific Data, vol.4, p.170117, 2017. ,
Identifying the Best Ma-chine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge, 2018. ,
A New Online Class-Weighting Approach with Deep Neural Networks for Image Segmentation of Highly Unbalanced Glioblastoma Tumors, International Work-Conference on Artificial Neural Networks, pp.555-567, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02172208
Receptive fields, binocular interaction and functional architecture in the cat's visual cortex, The Journal of physiology, vol.160, pp.106-154, 1962. ,
Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-GBM collection, The Cancer Imaging Archive, 2017. ,
Segmentation Labels and Radiomic Features for the Pre-operative Scans of the TCGA-LGG collection, The Cancer Imaging Archive, 2017. ,
U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer-assisted intervention, pp.234-241, 2015. ,
3D U-Net: learning dense volumetric segmentation from sparse annotation, International conference on medical image computing and computer-assisted intervention, pp.424-432, 2016. ,
V-net: Fully convolutional neural networks for volumetric medical image segmentation, 2016 Fourth International Conference on 3D Vision (3DV), pp.565-571, 2016. ,