Breaking medical data sharing boundaries by using synthesized radiographs-Reference-Cited by-同舟云学术

Breaking medical data sharing boundaries by using synthesized radiographs

Published:2020-12-04 Issue:49 Volume:6 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Han Tianyu¹^ORCID,Nebelung Sven²,Haarburger Christoph³,Horst Nicolas⁴,Reinartz Sebastian¹⁵^ORCID,Merhof Dorit⁴⁶⁷^ORCID,Kiessling Fabian⁶⁷⁸^ORCID,Schulz Volkmar¹⁶⁷^ORCID,Truhn Daniel³⁵^ORCID

Affiliation:

1. Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.

2. Department of Diagnostic and Interventional Radiology, University Hospital Düsseldorf, Düsseldorf, Germany.

3. Aristra GmbH, Berlin, Germany.

4. Institute of Imaging and Computer Vision, RWTH Aachen University, Aachen, Germany.

5. Department of Diagnostic and Interventional Radiology, University Hospital Aachen, Aachen, Germany.

6. Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.

7. Comprehensive Diagnostic Center Aachen (CDCA), University Hospital RWTH Aachen, Aachen, Germany.

8. Institute for Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.

Abstract

Distributed adversarial networks can generate synthesized radiographs, yielding better classification while maintaining privacy.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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