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. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: IEEE Trans Med Imaging. 2019 Dec 13;39(6):1856–1867. doi: 10.1109/TMI.2019.2959609

Fig. 7:

Fig. 7:

UNet++ can better segment tumors of various sizes than does U-Net. We measure the size of tumors based on the ground truth masks and then divide them into seven groups. The histogram shows the distribution of different tumor sizes. The box-plot compares the segmentation performances of U-Net (black) and UNet++ (red) in each group. The t-test for two independent samples has been further performed on each group. As seen, UNet++ improves segmentation for all sizes of tumors and the improvement is significant (p < 0.05) for the majority of the tumor sizes (highlighted in red).