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. 2023 Aug 16;13(10):6482–6492. doi: 10.21037/qims-23-233

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2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0.

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The fused results of the 2D and 3D models. (A) The 2D and (D) 3D model training loss curves. The 3 curves in the figure are the training (blue), validation loss (red), and results of the evaluation (green). The segmentation results of the (B) 2D and (E) 3D models. (C) The process of dilating the 2D model segmentation results. (F) The results of the fusion model. The red box represents the missegmentation, and the green box represents the correct segmentation.