Assessing the Ability of Generative Adversarial Networks to Learn Canonical Medical Image Statistics.

Authors:
Kelkar VA; Gotsis DS; Brooks FJ; Kc P; Myers KJ and 2 more

Journal:
IEEE Trans Med Imaging

Publication Year: 2023

DOI:
10.1109/TMI.2023.3241454

PMCID:
PMC10314718

PMID:
37022374

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Journal Information

Full Title: IEEE Trans Med Imaging

Abbreviation: IEEE Trans Med Imaging

Country: Unknown

Publisher: Unknown

Language: N/A

Publication Details

Subject Category: Diagnostic Imaging

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

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"This work was supported in part by the National Institute of Health (NIH) under Award R01EB031585 and Award P41EB031772. The work of Varun A. Kelkar was supported by the Research Participation Program at the Center for Devices and Radiological Health Administered by the Oak Ridge Institute for Science and Education through an Inter-Agency Agreement between the U.S. Department of Energy and U.S. Food and Drug Administration (FDA). (Corresponding author: Mark A. Anastasio.)"

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Last Updated: Aug 05, 2025