Retrospective measurements of muscular contraction in diffusion-weighted imaging are inherently asynchronous leading to an unknown time point of acquisition during the muscular motion. Therefore, prospective imaging is investigated based on surface electromyography signals derived during the measurement. Fast and more robust real-time activity detection is achieved by a neural network. Imaging during active muscular contraction can be prevented by analysis of the muscular state; however, sampling at different time points of the muscular contractions is also possible.
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