Table 6 Experimental results for the combined adult and child datasets, trained on a merged dataset consisting of both children’s and adult dental datasets (1663 training images, 306 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

0.9434

0.0261

0.9795

0.0114

0.9718

0.0080

0.8812

0.0310

0.9365

0.0183

R2 U-Net23

0.9300

0.0367

0.9839

0.0108

0.9719

0.0081

0.8828

0.0364

0.9373

0.0223

PSPNet24

0.9136

0.0197

0.9830

0.0046

0.9671

0.0063

0.8657

0.0230

0.9278

0.0138

Deeplab V3+25

0.9467

0.0213

0.9719

0.0125

0.9666

0.0086

0.8588

0.0321

0.9237

0.0192

  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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