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FLAIR (fluid attenuated inversion recovery) imaging via synthetic MRI methods leads to artifacts in the brain, which can cause diagnostic limitations. The main sources of the artifacts are attributed to… Click to show full abstract
FLAIR (fluid attenuated inversion recovery) imaging via synthetic MRI methods leads to artifacts in the brain, which can cause diagnostic limitations. The main sources of the artifacts are attributed to the partial volume effect and flow, which are difficult to correct by analytical modeling. In this study, a deep learning (DL)‐based synthetic FLAIR method was developed, which does not require analytical modeling of the signal.
Keywords:
mri flair;
data driven;
flair;
driven synthetic;
synthetic mri
Journal Title: Journal of Magnetic Resonance Imaging
Year Published: 2019
Link to full text (if available)
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Journal Title: Journal of Magnetic Resonance Imaging
Year Published: 2019
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!