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Purpose
To develop a deep neural network to recover filtered phase from clinical MR phase images to enable the computation of QSMs.
Methods
Eighteen deep learning networks were trained to recover combinations of 13 SWI phase‐filtering pipelines. SWI‐filtered data were computed offline from five multiorientation, multiecho MRI scans yielding 132 3D volumes (118/7/7 training/validation/testing)....
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