Web: http://arxiv.org/abs/2012.04764

May 5, 2022, 1:10 a.m. | Mohammad Havaei, Ximeng Mao, Yiping Wang, Qicheng Lao

cs.CV updates on arXiv.org arxiv.org

Synthetic medical image generation has a huge potential for improving
healthcare through many applications, from data augmentation for training
machine learning systems to preserving patient privacy. Conditional Adversarial
Generative Networks (cGANs) use a conditioning factor to generate images and
have shown great success in recent years. Intuitively, the information in an
image can be divided into two parts: 1) content which is presented through the
conditioning vector and 2) style which is the undiscovered information missing
from the conditioning vector. …

arxiv images inference medical

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