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MedGAN: Medical image translation using GANs.

Karim Armanious1, Chenming Jiang2, Marc Fischer1

  • 1University of Stuttgart, Institute of Signal Processing and System Theory, Stuttgart, Germany; University of Tübingen, Department of Radiology, Tübingen, Germany.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|December 8, 2019
PubMed
Summary

MedGAN is a novel framework for end-to-end medical image-to-image translation using generative adversarial networks (GANs). It achieves superior performance in tasks like PET-CT translation and MR artifact correction without task-specific tuning.

Keywords:
Deep neural networksGenerative adversarial networksImage translationMR motion correctionPET attenuation correction

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