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. 2021 Jul;11(7):3286–3305. doi: 10.21037/qims-20-1356

Table 6. Performance of the five best traditional and deep learning methods (see Tables 4,5) on the independent dataset (LIDC-IDRI).

Method DSC
U-Net-ResNet34 (full trained) 0.763±0.217
U-Net-MobileNet (full trained) 0.692±0.320
LinkNet-ResNet34 (full trained) 0.738±0.229
LinkNet-MobileNet (full trained) 0.745±0.221
PspNet-ResNet34 (full trained) 0.657±0.318
MorphACWE 0.704±0.256
Felzenszwalb 0.627±0.250
Watershed 0.503±0.350
MultiOtsu 0.610±0.271
MSER 0.465±0.272

LIDC-IDRI, Lung Image Database Consortium image collection; DSC, Sørensen-Dice coefficient; MorphACWE, morphological active contours without edges; MSER, maximally stable extremal regions.