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Purpose
To mitigate inhomogeneity at 7T for multi‐channel transmit arrays using unsupervised deep learning with convolutional neural networks (CNNs).
Methods
Deep learning parallel transmit (pTx) pulse design has received attention, but such methods have relied on supervised training and did not use CNNs for multi‐channel maps. In this work, we introduce an...
Multi‐contrast images are commonly acquired together to maximize complementary diagnostic information, albeit at the expense of longer scan times. A time‐efficient strategy to acquire high‐quality multi‐contrast images is to accelerate individual sequences and then reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms...
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