## 4 Discussion
The inaccuracy of CBCT-based detection methods is largely related to the image quality of radiography. Computed tomography implies an image-distortion phenomenon and the appearance of image artifacts because of zero transmission projections and beam-hardening effects [28]. When an X-ray image is projected onto metals, photon starvation can be triggered by full absorption of the low-energy X-ray quanta and interference occurs between the scattered photons [29]. Although several approaches--such as the projection of higher-energy quanta, use of a dual-energy system, and specific algorithms incorporating adaptive filtering of the raw data--have been introduced to reduce the image distortions and artifacts [30; 31], inherent limitations remain inevitable with any CBCT method. The quality of radiographic and 3D reconstruction images obtained by CBCT is also dependent on certain acquisition parameters, such as the object's position, field of view, tube voltage, tube current, device type, voxel size, signal-to-noise ratio, and gray value thresholds of segmentation [32; 33]. Thus the accuracy of CBCT-based detection methods may vary according to existing image artifacts and the scanning parameter conditions. Moreover, the radiographic image of implants is magnified and the lines in the image are blurred because of limited image resolution and the characteristics of the bitmap format [34]. When the radiographic image of an implant is converted to the mesh format, the contours of the implant are drawn with lines in the vector format in the analysis software. Clear contour lines of the implants could enhance image-matching between the planned and actual implant positions by reducing the presumptive selection of implant boundaries [35]. However, because the shape of the implant in the mesh format is fundamentally dependent upon the quality of the radiographic image of CBCT, the process of image conversion may not significantly improve the accuracy of the methodology in detecting the position of the implants. The results of our study also showed large linear and angular deviations of the implant position in the mesh model image. The errors in the scan abutment group might be derived from the manual tightening of the scan abutment and the image-matching algorithm of the CAD software program. Although manual tightening of the scan abutment using finger drivers is commonly performed in both the clinic setting and in research [20], the adaptation of the scan abutment to the implant could differ among operators. Accordingly, the use of electric torque drivers to eliminate the effects of unwanted confounding factors may be recommended. The accuracy of image-matching of the scan body in the software program should also be elucidated to systematically analyze the cause of errors resulting from the scan abutment method. One limitation of this study is that the in vitro nature of this investigation did not allow for the consideration of relevant clinical factors, such as the hard and soft tissue, various edentulous situations, and patient movement. Thus, further comprehensive randomized controlled clinical studies are necessary to confirm the results of this validation study.