Keywords
Convolution Neural Networks, fMRI, Classification, GPU
Abstract
The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.
Recommended Citation
Yang, Xin; Sarraf, Saman; and Zhang, Ning
(2018)
"Deep Learning-based framework for Autism functional MRI Image Classification,"
Journal of the Arkansas Academy of Science: Vol. 72, Article 11.
DOI: 10.54119/jaas.2018.7214
Available at:
https://scholarworks.uark.edu/jaas/vol72/iss1/11
Included in
Artificial Intelligence and Robotics Commons, Computational Neuroscience Commons, Other Computer Sciences Commons
