  In neuroimaging studies, the human cortex is commonly modeled as a sphere to
preserve the topological structure of the cortical surface. Cortical
neuroimaging measures hence can be modeled in spherical representation. In this
work, we explore analyzing the human cortex using spherical CNNs in an
Alzheimer's disease (AD) classification task using cortical morphometric
measures derived from structural MRI. Our results show superior performance in
classifying AD versus cognitively normal and in predicting MCI progression
within two years, using structural MRI information only. This work demonstrates
for the first time the potential of the spherical CNNs framework in the
discriminative analysis of the human cortex and could be extended to other
modalities and other neurological diseases.
