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. Author manuscript; available in PMC: 2022 Mar 3.
Published in final edited form as: IEEE Trans Med Imaging. 2022 Mar 2;41(3):543–558. doi: 10.1109/TMI.2021.3116879

Fig. 1.

Fig. 1.

Unsupervised learning strategy for contrast-agnostic registration. At every mini batch, we synthesize a pair of 3D label maps {sm, sf} and the corresponding 3D images {m, f} from noise distributions. The label maps are incorporated into a loss that is independent of image contrast.