Description

The goal of the present study was to apply deep learning algorithms to identify autism spectrum disorder (ASD) patients from large brain imaging dataset, based solely on the patient’s brain activation patterns. We investigated ASD patient’s brain imaging data from a world-wide multi-site database known as ABIDE (Autism Brain Imaging Data Exchange). In this system, autism dataset was collected from dataset repository. Then, we have to implement the pre-processing techniques. Then, the system is developed the deep learning algorithm such as CNN. The experimental results shows that accuracy and predict the given input image is normal or abnormal.