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Automated segmentation on the entire cardiac cycle using a deep learning work-flow
[article]
2018
arXiv
pre-print
The segmentation of the left ventricle (LV) from CINE MRI images is essential to infer important clinical parameters. Typically, machine learning algorithms for automated LV segmentation use annotated contours from only two cardiac phases, diastole, and systole. In this work, we present an analysis work-flow for fully-automated LV segmentation that learns from images acquired through the cardiac cycle. The workflow consists of three components: first, for each image in the sequence, we perform
arXiv:1809.01015v1
fatcat:jwv3zu34u5brdow2wosp7za2qa