Figure 1:

Training data required of the three types of harmonization methods. (a) Supervised harmonization methods (Dewey et al., 2019; Tian et al., 2022) require a sample group of subjects to be imaged across sites (i.e., inter-site paired data) for training. (b) Unsupervised methods developed for natural image I2I (Huang et al., 2018; Liu et al., 2018; Park et al., 2020; Zhu et al., 2017) can be trained with different subjects across sites. (c) Unsupervised harmonization methods with disentanglement (Ouyang et al., 2021; Zuo et al., 2021a,b) utilize the routinely acquired intra-site paired data for training.