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. 2021 Aug 20;25(11):4152–4162. doi: 10.1109/JBHI.2021.3106341

Fig. 4.

Fig. 4.

Visual comparison of COVID-19 infection segmentation by different methods on 2D COVID-SemiSeg dataset. As can be observed, our method can generate segmentation results with more accurate boundaries and less segmentation mistakes in small infection areas, which is closer to the ground truth.