Deep learning based joint fusion approach to exploit anatomical and functional brain information in autism spectrum disorders.

ABSTRACT:

Background

The integration of the information encoded in multiparametric MRI images can enhance the performance of machine-learning classifiers. In this study, we investigate whether the combination of structural and functional MRI might improve the performances of a deep learning (DL) model trained to discriminate subjects with Autism Spectrum Disorders (ASD) with respect to typically developing controls (TD).

Material and methods

We analyzed both structural and functional MRI brain scans publicly available within the ABIDE I and II data collections. We considered 1383 male subjects with age between 5 and 40 years, including 680 subjects with ASD and 703 TD from 35 different acquisition sites. We extracted morphometric and functional brain features from MRI scans with the F

SUBMITTER: Saponaro S 

PROVIDER: S-EPMC10776521 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature