Synthetic Medical Imaging Generation with Generative Adversarial Networks For Plain Radiographs

arXiv:2403.19107v1 Announce Type: cross
Abstract: In medical imaging, access to data is commonly limited due to patient privacy restrictions and the issue that it can be difficult to acquire enough data in the case of rare diseases.[1] The purpose of this investigation was to develop a reusable open-source synthetic image generation pipeline, the GAN Image Synthesis Tool (GIST), that is easy to use as well as easy to deploy. The pipeline helps to improve and standardize AI algorithms in the …

abstract adversarial arxiv case cs.cv cs.lg data diseases generative generative adversarial networks imaging investigation issue medical medical imaging networks patient privacy rare diseases restrictions synthetic type