Abstract:Despite advances in deep learning methods aimed at cardiac ventricular segmentation, most algorithms have drawbacks due to low prediction accuracy with images from different MR scans to those trained. It leads to a process that requires time-consuming correction by technicians or specialists. The time in this process is significant mainly due to the large number of image sets to be processed. The lack of description of the algorithms has not allowed repeatability, while commercial software is difficult to acce… Show more
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