- Patent Title: Methods, systems, and computer readable media for using a trained adversarial network for performing retrospective magnetic resonance imaging (MRI) artifact correction
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Application No.: US17127366Application Date: 2020-12-18
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Publication No.: US11360180B2Publication Date: 2022-06-14
- Inventor: Pew-Thian Yap , Siyuan Liu
- Applicant: The University of North Carolina at Chapel Hill
- Applicant Address: US NC Chapel Hill
- Assignee: The University of North Carolina at Chapel Hill
- Current Assignee: The University of North Carolina at Chapel Hill
- Current Assignee Address: US NC Chapel Hill
- Agency: Jenkins, Wilson, Taylor & Hunt, P.A.
- Main IPC: G01R33/565
- IPC: G01R33/565 ; A61B5/055

Abstract:
A method for performing retrospective magnetic resonance imaging (MRI) artifact correction includes receiving, as input, an MRI image having at least one artifact; using a trained adversarial network for performing retrospective artifact correction on the MRI image, wherein the trained adversarial network is trained using unpaired artifact-free MRI images and artifact-containing MRI images; and outputting, by the trained adversarial network, a derivative MRI image related to the input, wherein the at least one artifact is corrected in the derivative MRI image.
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