Detecting Invasive Ductal Carcinoma with Semi-supervised Conditional GANs

Citation:

Johnson JW. Detecting Invasive Ductal Carcinoma with Semi-supervised Conditional GANs, in Proceedings of the Future Technologies Conference (FTC) 2020, Volume 3. Cham: Springer International Publishing ; 2021 :113–120.

Abstract:

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 scores on a range of metrics over a baseline CNN.