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Detecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs
- Source :
- Proceedings of the Future Technologies Conference (FTC) 2020, vol. 3, pp.113-120
- Publication Year :
- 2019
-
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.<br />Comment: 5 pages, 3 figures
Details
- Database :
- arXiv
- Journal :
- Proceedings of the Future Technologies Conference (FTC) 2020, vol. 3, pp.113-120
- Publication Type :
- Report
- Accession number :
- edsarx.1911.06216
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/978-3-030-63092-8