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Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis
[article]
2017
arXiv
pre-print
Generative Adversarial Neural Networks (GANs) are applied to the synthetic generation of prostate lesion MRI images. GANs have been applied to a variety of natural images, is shown show that the same techniques can be used in the medical domain to create realistic looking synthetic lesion images. 16mm x 16mm patches are extracted from 330 MRI scans from the SPIE ProstateX Challenge 2016 and used to train a Deep Convolutional Generative Adversarial Neural Network (DCGAN) utilizing cutting edge
arXiv:1708.00129v1
fatcat:ucburqtk4zem5avrnx7pjvuska