Cardiac diffusion tensor imaging (cDTI) suffers from low signal-to-noise ratios, which results in tensor variability. In order to decrease tensor variability, the number of diffusion directions or number of averages must increase, consequently increasing the scan time. Recent implementations of artificial neural network (ANN) have proven that a non-linear mapping between diffusion signals and tensors is possible and can decrease tensor variability without increasing scan time. We implement an ANN tensor reconstruction for ex vivo porcine hearts to evaluate if a robust ANN diffusion tensor reconstruction is a beneficial technique to decrease tensor variability at no cost in scan time.
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