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Abstract #3364

A deep network for continuous motion detection during MRI scanning

Isabelle Heukensfeldt Jansen1, Sangtae Ahn1, Rafi Brada2, Michael Rotman2, and Christopher J. Hardy1
1GE Global Research Center, Niskayuna, NY, United States, 2GE Global Research Center, Herzliya, Israel

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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