In-vivo cardiac diffusion weighted images contain contrast differences that complicate image registration from multiple breath-holds. Additionally, neighbouring structures of the chest wall, liver and stomach do not move rigidly with the heart during the respiratory cycle which further hinders registration. In this work we remove other structures and pre-process the image with the help of a convolutional neural network trained to segment multiple heart structures. These additional steps increase the accuracy of registration of the left ventricular myocardial ring resulting in more accurate diffusion tensors.
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