Multiscale graph convolutional networks for cardiac motion analysis
We propose a multiscale spatio-temporal graph convolutional network (MST-GCN) approach to learn the left ventricular (LV) motion patterns from cardiac MR image sequences. The MST-GCN follows an encoder-decoder framework. The encoder uses a sequence of multiscale graph computation units (MGCUs). The...
| Autori principali: | , , , |
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| Natura: | Conference item |
| Lingua: | English |
| Pubblicazione: |
Springer
2021
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