New deep learning method boosts MRI results without requiring new data

A team of researchers from Washington University in St. Louis has found a new deep learning method that can minimize artifacts and other noise in MRI images that come from movement and a short image-acquisition time.

Deep learning learns directly from the training data how to determine the signal from artifacts and noise, or variations in signal intensity in an image. Many existing deep learning-based MRI reconstruction methods are able to remove artifacts and noise but they learn from a ground truth reference, which can be difficult to obtain.

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