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Erschienen in:
01.07.2016 | Original Article
Accuracy of 3D cephalometric measurements based on an automatic knowledge-based landmark detection algorithm
Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 7/2016
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Abstract
Purpose
To evaluate the accuracy of three-dimensional cephalometric measurements obtained through an automatic landmark detection algorithm compared to those obtained through manual identification.
Methods
The study demonstrates a comparison of 51 cephalometric measurements (28 linear, 16 angles and 7 ratios) on 30 CBCT (cone beam computed tomography) images. The analysis was performed to compare measurements based on 21 cephalometric landmarks detected automatically and those identified manually by three observers.
Results
Inter-observer ICC for each landmark was found to be excellent (\({>}0.9\)) among three observers. The unpaired t-test revealed that there was no statistically significant difference in the measurements based on automatically detected and manually identified landmarks. The difference between the manual and automatic observation for each measurement was reported as an error. The highest mean error in the linear and angular measurements was found to be 2.63 mm (\(\hbox {Or}_{\mathrm{L}}\hbox {-Or}_{\mathrm{R}}\) distance) and \(2.12^{\circ }\) (\(\hbox {Co}_{\mathrm{L}}\hbox {-Go}_{\mathrm{L}}\)-Me angle), respectively. The highest mean error in the group of distance ratios was 0.03 (for N-Me/N-ANS and \(\hbox {Go}_{\mathrm{R}}\hbox {-Gn/S-N}\)).
Conclusion
Cephalometric measurements computed from automatic detection of landmarks on 3D CBCT image were as accurate as those computed from manual identification.