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. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: IEEE Trans Med Imaging. 2021 Nov 30;40(12):3507–3518. doi: 10.1109/TMI.2021.3089547

TABLE IV.

Comparison among ResUnet, AttnUnet, CleftNet without feature augmentors (FAs), CleftNet without lable augmentor (LAs), and CleftNet in terms of CREMI-score, F1-Score, and AUC on the validation set.

Model CREMI-score(↓) AUC(↑) F1-score(↑)
ResUnet 59.64 0.909 0.874
AttnUnet 57.34 0.914 0.878
CleftNet w/o FA 53.37 0.922 0.883
CleftNet w/o LA 52.65 0.930 0.890
CleftNet 50.50 0.938 0.895