Keywords: Flow, SegmentationThe segmentation of large vessels in 4D Flow MRI remains a challenge, due to different problems such as random acquisition noise, low spatial and temporal resolution, velocity aliasing, respiratory motion, phase offsets. For that reason the use of a single segmentation has been standardized to represent the geometry throughout all the cardiac phases. However, recent studies have proposed the use of image registration to be able to solve this problem. In this work, an algorithm based on a medical image registration neural network is proposed to improve the segmentation over time for the cardiac phases of the systole period.
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