We introduce ISHMAPS, a method for detecting and adapting to patient motion in real time during an MR scan. The method uses a neural network trained on motion-corrupted data to detect and score motion using as little as 6% of k-space. Once motion is detected, multiple separate complex sub-images from different motion states can be reconstructed and combined into a motion-free image, or the scan can adaptively re-acquire sections of k-space taken before motion occurred.
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