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Table 6 Statistical results for the multi segmentor

From: COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet

Net. Class Sens. Spec. Dice. G-mean F2
SegNet \({\hbox {C}}_1\) 0.638 .0.952 0.479 0.780 0.562
\({\hbox {C}}_2\) 0.672 0.965 0.454 0.806 0.564
\({\hbox {C}}_3\) 0.574 0.988 0.121 0.753 0.231
U-NET \({\hbox {C}}_1\) 0.804 0.930 0.483 0.865 .0.636
\({\hbox {C}}_2\) 0.694 0.983 0.597 0.826 0.652
\({\hbox {C}}_3\) 0.684 0.993 0.225 0.824 0.377
  1. Bold values indicate the highest number of a comparable set
  2. SegNet and U-NET multi class segmentation tools results is terms of sensitivity, specificity, dice, G-mean, and F2 score. Matching color rows display the results for the same class