Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices

@article{Dodero2015KernelbasedCF,
  title={Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices},
  author={Luca Dodero and Ha Quang Minh and Marco San-Biagio and Vittorio Murino and Diego Sona},
  journal={2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)},
  year={2015},
  pages={42-45}
}
An important task in connectomics studies is the classification of connectivity graphs coming from healthy and pathological subjects. In this paper, we propose a mathematical framework based on Riemannian geometry and kernel methods that can be applied to connectivity matrices for the classification task. We tested our approach using different real datasets of functional and structural connectivity, evaluating different metrics to describe the similarity between graphs. The empirical results… CONTINUE READING