scholarly journals Automatic calibration method of voxel size for cone-beam 3D-CT scanning system

2014 ◽  
Vol 38 (4) ◽  
pp. 046202 ◽  
Author(s):  
Min Yang ◽  
Xiao-Long Wang ◽  
Yi-Peng Liu ◽  
Fan-Yong Meng ◽  
Xing-Dong Li ◽  
...  
2011 ◽  
Vol 31 (12) ◽  
pp. 1212004
Author(s):  
李兴东 Li Xingdong ◽  
杨民 Yang Min ◽  
李德红 Li Dehong ◽  
刘文丽 Liu Wenli

2012 ◽  
Vol 52 ◽  
pp. 16-22 ◽  
Author(s):  
Min Yang ◽  
Jianhai Zhang ◽  
Maodan Yuan ◽  
Xingdong Li ◽  
Wenli Liu ◽  
...  

2011 ◽  
Vol 204-210 ◽  
pp. 493-497
Author(s):  
Sheng Yong Xu ◽  
De Hua Li ◽  
Zhu Li ◽  
Qing Wei

Calibration is an essential work in three-dimensional scanning system. The operation of existing calibration is complex and tedious. In this paper, we design a DLT-based automatic method of calibration, in which the calibration reference points are detected automatically. Then we can figure out a series of calibration parameters from these points. The average value of all parameters is just the calibration parameters. The experimental results show that the method we proposed is not only guaranteeing the calibration precision but also simplifying the calibration operation comparing with the traditional manual calibration method.


2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Mehmet Hakan Kurt ◽  
Nilsun Bağış ◽  
Cengiz Evli ◽  
Cemal Atakan ◽  
Kaan Orhan

Abstract Background To examine the influence of voxel sizes to detect of peri-implant fenestration defects on cone beam computed tomography (CBCT) images. Materials and methods This study performed with three sheep heads both maxilla and mandible and two types of dental implant type 1 zirconium implant (Zr40) (n = 6) and type 2 titanium implant (Ti22) (n = 10). A total of 14 peri-implant fenestrations (8 buccal surfaces, 6 palatal/lingual surface) were created while 18 surfaces (8 buccal, 10 palatal/lingual) were free of fenestrations. Three observers have evaluated the images of fenestration at each site. Images obtained with 0.75 mm3, 0.100 mm3, 0.150 mm3, 0.200 mm3, and 0.400 mm3 voxel sizes. For intra- and inter-observer agreements for each voxel size, Kappa coefficients were calculated. Results Intra- and inter-observer kappa values were the highest for 0.150 mm3, and the lowest in 0.75 mm3 and 0.400 mm3 voxel sizes for all types of implants. The highest area under the curve (AUC) values were found higher for the scan mode of 0.150 mm3, whereas lower AUC values were found for the voxel size for 0.400 mm3. Titanium implants had higher AUC values than zirconium with the statistical significance for all voxel sizes (p ≤ 0.05). Conclusion A voxel size of 0.150 mm3 can be used to detect peri-implant fenestration bone defects. CBCT is the most reliable diagnostic tool for peri-implant fenestration bone defects.


2021 ◽  
Author(s):  
Masoumeh Eftekhar ◽  
Hanieh Kaviani ◽  
Nina Rouzmeh ◽  
Aitin Torabinia ◽  
Alireza Akbarzadeh Baghban

Author(s):  
Ahmad M. R. Baydoun ◽  
Ramsey F. Hamade

Abstract Friction stir welding (FSW) is a novel welding method that is garnering attention, in part, due to its ability to join dissimilar materials. One of the challenges in producing dissimilar friction welded joints is ensuring the welds are defect-free. Nondestructive testing (NDT) methods such as ultrasonic waves, gamma rays, X-rays, and X-ray CT, are gaining popularity as a method to detect internal defects in FSW joints. In this study, dissimilar AA1050-AA6061-T6 FSW lap welds are Manufactured and then examined using an NDT X-ray CT technique. The effects of two critical X-ray CT scanning parameters (voxel size and Hounsfield unit (HU)) on the detection of internal defects are investigated. The samples are scanned via X-ray CT at two different voxel sizes (2.457 E−02 and 1.420 E−03 mm3) and two HU ranges (12-bit and 16-bit depth). The generated Digital Imaging and Communications in Medicine (DICOM) images are segmented based on a proper HU threshold found via the Otsu thresholding method. The findings show that Small voxel size (higher resolution) improves the ability of detecting internal defects and improves the effectiveness of the thresholding process. Higher HU range results in a wider separation between detected material peaks, thus enhancing the effectiveness of the thresholding process as well.


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