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TOP-GAN: Label-Free Cancer Cell Classification Using Deep Learning with a Small Training Set
[article]
2018
arXiv
pre-print
We propose a new deep learning approach for medical imaging that copes with the problem of a small training set, the main bottleneck of deep learning, and apply it for classification of healthy and cancer cells acquired by quantitative phase imaging. The proposed method, called transferring of pre-trained generative adversarial network (TOP-GAN), is a hybridization between transfer learning and generative adversarial networks (GANs). Healthy cells and cancer cells of different metastatic
arXiv:1812.11006v1
fatcat:kfqsz3bkbresnkcqkji4j734wu