DeepMedic for Brain Tumor Segmentation

@inproceedings{Kamnitsas2016DeepMedicFB,
  title={DeepMedic for Brain Tumor Segmentation},
  author={K. Kamnitsas and E. Ferrante and S. Parisot and C. Ledig and A. Nori and A. Criminisi and D. Rueckert and B. Glocker},
  booktitle={BrainLes@MICCAI},
  year={2016}
}
  • K. Kamnitsas, E. Ferrante, +5 authors B. Glocker
  • Published in BrainLes@MICCAI 2016
  • Computer Science
  • Accurate automatic algorithms for the segmentation of brain tumours have the potential of improving disease diagnosis, treatment planning, as well as enabling large-scale studies of the pathology. In this work we employ DeepMedic [1], a 3D CNN architecture previously presented for lesion segmentation, which we further improve by adding residual connections. We also present a series of experiments on the BRATS 2015 training database for evaluating the robustness of the network when less training… CONTINUE READING

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