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Abstract #4713

Exploration on deep-learning based sorting of k-space data for ECG-free cardiac cine-MRI

Seb Harrevelt1, Tim Leiner2, J.P.W. Pluim3, and A.J.E. Raaijmakers2

1TU Eindhoven, Delft, Netherlands, 2UMC Utrecht, Utrecht, Netherlands, 3TU Eindhoven, Eindhoven, Netherlands

Cine-cardiac MRI reconstruction relies on the ECG signal to sort k-space data. However, ECG triggering comes with disadvantages among which increased setup time. Here we suggest an alternative method of sorting cine MRI k-space data using deep-learning. An explorative study has been performed using an encoder-decoder network with Sinkhorn layer to sort k-space data that was randomly disordered in one spatial dimension. Good reconstructions were obtained using a group size of 8 or more k-space lines during randomization. These results hold promise for subsequent application in the time dimension.

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