Dynamic spatio-temporal graph convolutional networks for cardiac motion analysis
We propose a dynamic spatio-temporal graph convolutional network (DST-GCN) approach to learn the left ventricular (LV) motion patterns from cardiac MR cine images. We represent the myocardial geometry using a graph that is constructed from sample nodes on endo- and epicardial contours. The DST-GCN f...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2021
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