Dectecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs

@article{Johnson2019DectectingID,
  title={Dectecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs},
  author={Jeremiah W. Johnson},
  journal={ArXiv},
  year={2019},
  volume={abs/1911.06216}
}
Invasive ductal carcinoma (IDC) comprises nearly 80% of all breast cancers. The detection of IDC is a necessary preprocessing step in determining the aggressiveness of the cancer, determining treatment protocols, and predicting patient outcomes, and is usually performed manually by an expert pathologist. Here, we describe a novel algorithm for automatically detecting IDC using semi-supervised conditional generative adversarial networks (cGANs). The framework is simple and effective at improving… 

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