Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

@inproceedings{Meszlnyi2017RestingSF,
  title={Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture},
  author={Regina Meszl{\'e}nyi and Krisztian Buza and Zolt{\'a}n Vidny{\'a}nszky},
  booktitle={Front. Neuroinform.},
  year={2017}
}
Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a… CONTINUE READING