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Apparatus and method for deep learning to mitigate artifacts arising in simultaneous multi slice (SMS) magnetic resonance imaging (MRI)
Apparatus and method for deep learning to mitigate artifacts arising in simultaneous multi slice (SMS) magnetic resonance imaging (MRI)
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机译:深度学习的装置和方法减轻同时多切片(SMS)磁共振成像(MRI)中产生的伪影
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摘要
A deep learning (DL) network is proposed to mitigate artifacts in simultaneous multi-slice (SMS) magnetic resonance imaging (MRI) data. For example, unaliased images generated from SMS aliased images can exhibit leakage artifacts due to inaccuracies in the receive-coil sensitives used during sensitivity encoding (SENSE) processing. To mitigate leakage artifacts, the DL network learns to correct the receive-coil sensitives before SENSE processing, and/or learns to detect and subtract the artifacts from the unaliased images after SENSE processing. The DL network can also be trained to denoise the unaliased images.
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