Table 2.

Representative registration methods for infant brain images.

Study	Dataset	Modality	Applied infant ages	Method
(a) Intensity-based approaches
(Wei et al., 2017)	24 infants (leave-two-out validation)	T1w or T2w	2 W to 12 M, 3 M to 12 M, 6 M to 12 M, 9 M to 12 M	Learning based method using random forest and auto-context
(Wang et al., 2014c)	9 infants (leave-one-out validation)	T1w or T2w	2 W to 6 M, 6 M to 12 M	Sparse learning based method
(Wu et al., 2015)	24 infants (leave-one-out validation)	T1w or T2w	2 W to 12 M, 3 M to 12 M, 6 M to 12 M, 9 M to 12 M	Longitudinal-image-guided correspondence detection
(b) Segmentation-based approaches
(Wang et al., 2012a)	28 infants	T1w, T2w, FA	2 W, 3 M, 6 M, 9 M, 12 M	Tissue maps based method
(Shi et al., 2010a)	10 infants (leave-one-out validation)	T1w and T2w	Neonate, 1 Y, 2 Y	Tissue maps based method
(Ha et al., 2011)	10 infants	T1w	Neonate to 2 Y	Tissue maps and geometric descriptors based method
(c) Hybrid approaches
(Dong et al., 2017)	10 infants (leave-two -out validation)	T1w and T2w	2 W to 12 M, 3 M to 12 M, 6 M to 12 M, 2 W to3 M, 2 W to 6 M, 3 M to 6 M	Joint segmentation and registration

(W: weeks; M: months; Y: years; GA: gestational age)