Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis [article]

Andy Kitchen, Jarrel Seah
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
more » ... chniques. Synthetic outputs are compared to real images and the implicit latent representations induced by the GAN are explored. Training techniques and successful neural network architectures are explained in detail.
arXiv:1708.00129v1 fatcat:ucburqtk4zem5avrnx7pjvuska