Table 11.

Representative diffusion-weighted atlases for the infant brain.

Study	Age	Modality/ Diffusion Model	Components	Atlas name	Link
(Akazawa et al., 2016; Oishi et al., 2013; Oishi et al., 2011)	0 – 4 D	T1w, T2w, DW / Diffusion tensor model	Templates, WM Parcellation Map, Fiber Probability Map	JHU Neonatal Atlas	http://cmrm.med.jhmi.edu/
(Oishi et al., 2013)	18 , 24 M	T1w, T2w, DW / Diffusion tensor model	Templates, WM Parcellation Map	JHU Pediatric Atlas	http://cmrm.med.jhmi.edu/
(Bai et al., 2012; Broekman et al., 2014)	5 – 17 D	T2w, DW / No specific model	Templates	NUS Neonatal Atlas	http://www.bioeng.nus.edu.sg/cfa/infant_atlas.html
-	6 M	T2w, DW / No specific model	Templates	NUS Pediatric Atlas	http://www.bioeng.nus.edu.sg/cfa/infant_atlas.html
(Blesa et al., 2016)	39 – 47 W PA	T1w, T2w, DW / Diffusion tensor model	Templates, AAL parcellation map, Tissue probability map	UE Neonatal Atlas	http://brain-development.org/brain-atlases/neonatal-brain-atlas-albert/
(Saghafi et al., 2017)	14 – 48 D	DW / No specific model	Templates	UNC-CH Neonatal Atlas
(Kim et al., 2017)	0, 3, 6, 9, 12 M	DW / No specific model	Templates, Fiber probability map	UNC-CH Longitudinal Infant Atlas*

(D: days; W: weeks; M: months; WM: white matter; PA: postmenstrual age)

^*Brain atlas based on longitudinal dataset

Abbreviations: JHU. Johns Hopkins University; NUS. National University of Singapore; UE. University of Edinburgh; UNC-CH. University of North Carolina at Chapel Hill; AAL. Automated Anatomical Labeling.