Authors
Y ElNakieb, Matthew Nitzken, Ahmed Shalaby, Omar Dekhil, Ali Mahmoud, Andy Switala, Adel Elmaghraby, Robert Keynton, Mohammed Ghazal, Ashraf Khalil, Gregory Barnes, Ayman El-Baz
Publication date
2018/8/20
Conference
2018 24th International Conference on Pattern Recognition (ICPR)
Pages
3862-3867
Publisher
IEEE
Description
The ultimate goal of this paper is to develop a novel personalized comprehensive computer aided diagnostic (CAD) system for precise diagnosis of autism spectrum disorder (ASD) based on the 3D shape analysis of the cerebral cortex (Cx), To achieve the main goal of the proposed system, we used structural MRI modality (sMRI) to be able to extract the shape features of the brain cortex. After segmenting the brain cortex from sMRI, we used a spherical harmonics analysis to measure the surface complexity, in addition to studying surface curvatures. Finally, a multi-stage deep network based on several autoencoders and softmax classifiers is constructed to provide the final global diagnosis. The presented CAD system was tested on several datasets, achieving an average accuracy of 92.15%. In addition to its global diagnostic accuracy, the local diagnostic accuracies of the most significant areas also demonstrated …
Total citations
201920202021202213
Scholar articles
Y ElNakieb, M Nitzken, A Shalaby, O Dekhil… - 2018 24th International Conference on Pattern …, 2018