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Table 4 Comparison between the proposed method and previous studies on dental age assessment using dental panoramic images

From: Fully automated method for dental age estimation using the ACF detector and deep learning

Authors

Input

Automated type

Data

Stage assessment

Age estimation performance (difference and correlation between estimated age and chronological age)

Age range of samples (years)

No. of images

Demirjian’s method

Accuracy

Zaborowicz et.al., (2022)

Extracted tooth and bone parameters using ImageJ software

Semi

4–15

619

-

-

Difference: median absolute error = 1.48 years and mean absolute error = 4.61 months

Correlation: R2 = 0.93

Vila-Blanco et.al., (2020)

Full image

Fully

4.5–89.2

2289

-

-

Difference: median absolute error = 1.48 years and mean absolute error = 2.84 years

Correlation: R2 = 0.90

Hou et.al., (2021)

Full image

Fully

0–90

27,957

-

-

Difference: mean absolute error = 1.64 years

Atas et.al., (2022)

Full image

Fully

8–68

1332

-

-

Difference: mean absolute error = 3.13 years

Correlation: R2 = 0.87

Milošević et.al., (2022)

Specific teeth image

Full images: fully

Individual teeth: semi

19–90

4035

-

-

Difference: median absolute error = 2.95 years for full images, median absolute error = 4.68 years for individual teeth

De Tobel et.al., (2017)

Specific teeth image

Semi

7–24

400

10 stages (modified)

51.00%

-

Merdietio Boedi et.al., (2020)

Specific teeth image

Semi

7–24

400

10 stages (modified)

61.00%

-

Banar et.al., (2020)

Specific teeth image

Fully

7–24

400

10 stages (modified)

54.00%

-

Upalananda et.al., (2021)

Specific teeth image

Semi

15–23

2235

5 stages (D to H)

82.50%

Correlation: Spearman’s rank correlation r = 0.87, p < 0.001

Proposed method

Specific teeth image

Fully

15–23

1000

5 stages (D to H)

83.25%

Difference: median absolute error = 1.72 years and mean absolute error = 1.94 years

Correlation: Pearson’s linear correlation ρ = 0.91, p < 0.05