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2017

Conditional Adversarial Network for Semantic Segmentation of Brain Tumor

Rezaei, Mina, Harmuth, Konstantin, Gierke, Willi et al.

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Automated medical image analysis has a significant value in diagnosis and treatment of lesions.

Brain tumors segmentation has a special importance and difficulty due to the difference in appearances and shapes of the different tumor regions in magnetic resonance images.
Additionally, the data sets are heterogeneous and usually limited in size in comparison with the computer vision problems.
The recently proposed adversarial training has shown promising results in generative image modeling.

Conditional Adversarial Network for Semantic Segmentation of Brain Tumor · Around

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Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. CoRR abs/1511.06434 (2015), http://arxiv.org/abs/1511.06434
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