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In this paper, we present a data augmentation method that generates synthetic medical images using Generative Adversarial Networks (GANs).
“A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier,”
M. Gletsos et al., · 2003
Earlier work this paper cites.
“Imagenet classification with deep convolutional neural networks,”
A. Krizhevsky, Ilya I. Sutskever, and G. Hinton, · 2012
Earlier work this paper cites.
“Generative adversarial nets,”
I. Goodfellow et al., · 2014
Earlier work this paper cites.
“Unsupervised representation learning with deep convolutional generative adversarial networks,”
A. Radford, L. Metz, and S. Chintala, · 2015
Earlier work this paper cites.
“Cancer incidence and mortality worldwide: sources, methods and major patterns in globocan 2012,”
J. Ferlay et al., · 2015
Cited alongside, same era.
“Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique,”
H. Greenspan, B. van Ginneken, and R. M. Summers, · 2016
Cited alongside, same era.
“Conditional image synthesis with auxiliary classifier gans,”
A. Odena, C. Olah, and J. Shlens, · 2016
Cited alongside, same era.
“Towards adversarial retinal image synthesis,”
P. Costa et al., · 2017
Cited alongside, same era.
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
D. Nie et al., · 2017
Later among the works it cites.
“Unsupervised anomaly detection with generative adversarial networks to guide marker discovery,”
T. Schlegl et al., · 2017
Later among the works it cites.
“Computer-aided diagnosis of liver tumors on computed tomography images,”
C. Chang et. al, · 2017
Later among the works it cites.
“Task-driven dictionary learning based on mutual information for medical image classification,”
I. Diamant et al., · 2017
Later among the works it cites.
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