Geometric distortion of panoramic reconstruction in third molar tilting assessments: a comprehensive evaluation

Abstract

To evaluate the geometric distortion of tilting of mandibular third molars with respect to second molars on panoramic reconstruction. Methods: Cone-beam CT (CBCT) reconstructions of 160 third molars, obtained due to an indication of risk of inferior alveolar nerve damage during surgery, were used. CBCT-reconstructed panoramic images were used as bi-dimensional (2D) images, to avoid distortions other than geometric distortions. The angle between the second and the third molar was measured in 2D and three-dimensional (3D) images. Student's t-test was used to assess the null-hypothesis of no difference between 2D and 3D measurements. Results: A significant mean difference (−2.3° ± 6.3°) between 2D and 3D measurements was found, with an absolute error of 3.6° ± 5.7° and a relative error of 10%. These findings comprehensively explain the geometric distortion on panoramic radiographs. conclusions: Although a widely used and undoubtedly useful tool for diagnosis and surgical planning of mandibular third molar extractions, panoramic reconstruction are biased from geometric distortion that may influence surgical planning.

Radiographic prediction of mandibular third molar eruption and mandibular canal involvement based on angulation

“…One must be aware of the geometric distortion of the dental arch on a panoramic image . Additionally, positional errors when placing the patient in the panoramic X‐ray machine may result in discrepancies between the molar angulation measurements at T1 and T2.…”

Micro-Distortion Detection of Lidar Scanning Signals Based on Geometric Analysis

“…In order to test the detection time and the detection degree of the proposed geometric statistics-based micro-distortion detection technology for lidar scanning signals, the experiment was compared with methods in [8,9]. The experimental platform was built by the control host of Intel B360 i7-8700.…”

“…Through experiments, time-consuming results of the three methods were recorded, as shown in Table 1. The proposed method and methods in [8,9] were used to detect the micro-distortion of 3000 sets for lidar scanning signals. Through experiments, time-consuming results of the three methods were recorded, as shown in Table 1.…”

“…com). Using the proposed method and methods in [8,9], the micro-distortion of the lidar scanning signal was detected in a strong interference environment. The three-dimensional output of the three methods is shown in Figure 7.…”

“…g (k ) is a micro-distortion signal input without a lidar scanning signal. L , M are the observer gain matrix and controller gain matrix for minor distortion correction, respectively [9]. The combined variable τ(k ) obeyed Bernoulli distribution, and the statistical signal features were:…”