BMC Medical Imaging (Mar 2020)

The application and accuracy of feature matching on automated cephalometric superimposition

  • Yiran Jiang,
  • Guangying Song,
  • Xiaonan Yu,
  • Yuanbo Dou,
  • Qingfeng Li,
  • Siqi Liu,
  • Bing Han,
  • Tianmin Xu

DOI
https://doi.org/10.1186/s12880-020-00432-z
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 7

Abstract

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Abstract Background The aim of this study was to establish a computer-aided automated method for cephalometric superimposition and to evaluate the accuracy of this method based on free-hand tracing. Methods Twenty-eight pairs of pre-treatment (T1) and post-treatment (T2) cephalograms were selected. Structural superimpositions of the anterior cranial base, maxilla and mandible were independently completed by three operators performing traditional hand tracing methods and by computerized automation using the feature matching algorithm. To quantitatively evaluate the differences between the two methods, the hand superimposed patterns were digitized. After automated and hand superimposition of T2 cephalograms to T1 cephalometric templates, landmark distances between paired automated and hand T2 cephalometric landmarks were measured. Differences in hand superimposition among the operators were also calculated. Results The T2 landmark differences in hand tracing between the operators ranged from 0.61 mm to 1.65 mm for the three types of superimposition. There were no significant differences in accuracy between hand and automated superimposition (p > 0.05). Conclusions Computer-aided cephalometric superimposition provides comparably accurate results to those of traditional hand tracing and will provide a powerful tool for academic research.

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