Modelling cardiac motion via spatio-temporal graph convolutional networks to boost the diagnosis of heart conditions
We present a novel spatio-temporal graph convolutional networks (ST-GCN) approach to learn spatio-temporal patterns of left ventricular (LV) motion in cardiac MR cine images for improving the characterization of heart conditions. Specifically, a novel GCN architecture is used, where the sample nodes...
| Main Authors: | , , , |
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| Formato: | Conference item |
| Idioma: | English |
| Publicado em: |
Springer
2021
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