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. Author manuscript; available in PMC: 2022 Oct 1.
Published in final edited form as: IEEE Trans Med Imaging. 2021 Sep 30;40(10):2857–2868. doi: 10.1109/TMI.2021.3060634

Fig. 4.

Fig. 4.

Fine-tuning from TransVW provides better optimization and accelerates the training process in comparison with training from scratch as well as state-of-the-art Models Genesis [5], as demonstrated by the learning curves for the five 3D target tasks. All models are evaluated on the validation set, and the average accuracy and dice-coefficient over ten runs are plotted for the classification and segmentation tasks, respectively.