Table 5 Experimental results for the adult datasets, trained exclusively on the adult dental dataset (1500 training images, 276 test images).

From: Children’s dental panoramic radiographs dataset for caries segmentation and dental disease detection

 

Recall

Specificity

ACC

IOU

Dice

mean

std

mean

std

mean

std

mean

std

mean

std

U-Net22

0.9459

0.0231

0.9795

0.0119

0.9719

0.0083

0.8858

0.0274

0.9392

0.0162

R2 U-Net23

0.9351

0.0268

0.9838

0.0112

0.9724

0.0079

0.8892

0.0264

0.9411

0.0156

PSPNet24

0.9164

0.0175

0.9827

0.0044

0.9670

0.0063

0.8693

0.0201

0.9299

0.0122

Deeplab V3+25

0.9465

0.0218

0.9721

0.0130

0.9665

0.0088

0.8639

0.0284

0.9267

0.0171

  1. Evaluation metrics include Recall, Specificity, Accuracy, Intersection over Union (IOU), and Dice index, with mean and standard deviation (std) values provided.
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