Table 1.

Magnetic resonance imaging (MRI)/functional MRI (fMRI).

Reference	Focus	N participants	Age	Input data/device used	Method used	Dataset
Samson et al.22	fMRI to study the neural bases of complex non-social sound processing	15 ASD, 13 TD	ASD: 24.3 ± 6.25 TD: 23.5 ± 7.42	fMRI scans/3 T TRIO MRI system	Image processing/ICBM152 (MNI) space and 3D Gaussian Filtering	Own dataset
Abdelrahman et al.23	MRI for diagnosis	14 ASD, 28 TD	7-38 years	MRI scans/1.5 T Sigma MRI scanner	Mesh processing	Own dataset
Durrleman et al.24	MRI for biomarker detection	51 ASD, 25 TD and developmentally delayed children	18-35 months	MRI, 1.5-T GE Signa MRI scanner		122
Ahmadi et al.25	fMRI for biomarker detection	24 ASD, 27 TD		MRI scans/3T MRI scanner	Machine learning, independent component analysis	Own dataset
Chaddad et al.26	MRI for biomarker detection	34 ASD, 30 TD	4-24 years	MRI scans/3T MRI scanner	Texture analysis	ABIDE I dataset
Chaddad et al.27	MRI for biomarker detection	539 ASD, 573 TD	ASD: 17.01 ± 8.36 TD: 17.08 ± 7.72	MRI scans	Texture analysis	ABIDE I dataset
Eslami and Saeed28	fMRI for diagnosis	187 ASD, 183 TD		fMRI scans	Deep learning, MLP with 2 hidden layers + SVM	Four datasets (NYU, OHSU, USM, UCLA) from ABIDE-I fMRI dataset
Li et al.29	fMRI for diagnosis	149 ASD, 161 TD		rs-fMRI scans	Deep learning/SSAE	4 datasets (UM, UCLA, USM, LEUVEN) from ABIDE MRI dataset
Crimi et al.30	fMRI for diagnosis	31 ASD, 23 TD		Imaging data, GE 3T MR750 scanner	Machine Learning/Constrained Autoregressive Model	San Diego State University cohort of ABIDE II dataset
Chanel et al.32	fMRI for diagnosis	15 ASD, 14 TD	ASD: 28.6 ± 1.87 TD: 31.6 ± 2.61	fMRI/3T MRI scanner	Machine learning/SVM	Own dataset
Zheng et al.34	MRI for biomarker detection	66 ASD, 66 TD		MRI scans	multi-feature-based networks (MFN) and SVM	4 datasets (NYU, SBL, KUL, ISMMS) from ABIDE database