Invention Grant
- Patent Title: Motion artifact reduction of magnetic resonance images with an adversarial trained network
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Application No.: US16008086Application Date: 2018-06-14
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Publication No.: US10698063B2Publication Date: 2020-06-30
- Inventor: Sandro Braun , Boris Mailhe , Xiao Chen , Benjamin L. Odry , Pascal Ceccaldi , Mariappan S. Nadar
- Applicant: Siemens Healthcare GmbH
- Applicant Address: DE Erlangen
- Assignee: Siemens Healthcare GmbH
- Current Assignee: Siemens Healthcare GmbH
- Current Assignee Address: DE Erlangen
- Main IPC: G01R33/565
- IPC: G01R33/565 ; G06T5/00 ; G06N5/04 ; G06T7/20 ; G06N3/08

Abstract:
Systems and methods are provided for correcting motion artifacts in magnetic resonance images. An image-to-image neural network is used to generate motion corrected magnetic resonance data given motion corrupted magnetic resonance data. The image-to-image neural network is coupled within an adversarial network to help refine the generated magnetic resonance data. The adversarial network includes a generator network (the image-to-image neural network) and a discriminator network. The generator network is trained to minimize a loss function based on a Wasserstein distance when generating MR data. The discriminator network is trained to differentiate the motion corrected MR data from motion artifact free MR data.
Public/Granted literature
- US20190128989A1 MOTION ARTIFACT REDUCTION OF MAGNETIC RESONANCE IMAGES WITH AN ADVERSARIAL TRAINED NETWORK Public/Granted day:2019-05-02
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