CGAT, a graph attention network with a CLS node, achieves 0.76 weighted F1 on Demirjian stage classification of 3D third-molar meshes and generates attention maps that highlight roots and furcation regions.
IEEE Access8, 35929–35949 (2020)
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Attention Maps in 3D Shape Classification for Dental Stage Estimation with Class Node Graph Attention Networks
CGAT, a graph attention network with a CLS node, achieves 0.76 weighted F1 on Demirjian stage classification of 3D third-molar meshes and generates attention maps that highlight roots and furcation regions.