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AssigneeSiemens Healthineers AG
InventorsShujaat Khan, Mahmoud Mostapha, Mariappan S. Nadar, Thorsten Feiweier, Bryan Clifford, Mengwei Ren
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For distortion correction in magnetic resonance (MR) echo planar imaging (EPI), a combination of supervised and unsupervised training provides deep learning with generalized applicability across different use cases as well as sufficient training data (e.g., less ground truth data is needed due to the inclusion of unsupervised learning). The neural network for displacement estimation may include deformable convolution and/or layers for a non-diffeomorphic displacement field. The network architecture features and/or combined supervised and unsupervised learning may be used together or individually.
A method of machine training for magnetic resonance (MR) distortion correction in echo planar imaging, the method comprising:
A system for distortion correction in magnetic resonance echo planar imaging, the system comprising:
A system for distortion correction in magnetic resonance echo planar imaging, the system comprising:
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