Fig. 1.

Architecture for the ASD classification task. To initiate our analysis, we begin by capturing views of the unique characteristics of each cerebral hemisphere - the left and the right - as they are projected onto the spherical surface. The vantage point follow an icosahedron subdivision. We use a feature extraction network (resnet18, SpectFormer) on each individual view. We experiment with different IcoConv (IcoConv for icosahedron and convolution) operators that pool the information from all views. Finally, we concatenate the left/right outputs and normalized demographics. We perform a final linear layer for the classification.