Motion artifact reduction in fan-beam and cone-beam computed tomography via the fan-beam data consistency condition (FDCC)

2007 ◽  
Author(s):  
Shuai Leng ◽  
Brian Nett ◽  
Michael Speidel ◽  
Guang-Hong Chen
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Consistency Condition ◽  
Motion Artifact ◽  
Data Consistency ◽  
Cone Beam ◽  
Artifact Reduction

scholarly journals Efficacy of metal artifact reduction algorithm of cone-beam computed tomography for detection of fenestration and dehiscence around dental implants (Preprint)

2020 ◽  
Author(s):  
Fatemeh Salemi ◽  
Mohamad Reza Jamalpour ◽  
Amir Eskandarloo ◽  
Leili Tapak ◽  
Narges Rahimi
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Roc Curve ◽  
Titanium Implants ◽  
Cone Beam ◽  
Kappa Statistics ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Sensitivity Specificity

UNSTRUCTURED This study aimed to assess the efficacy of metal artifact reduction (MAR) algorithm of two cone-beam computed tomography (CBCT) systems for detection of peri-implant fenestration and dehiscence. Thirty-six titanium implants were placed in bone blocks of bovine ribs. Fenestration and dehiscence were created in the buccal bone around implants using a round bur. The bone blocks were then mounted in a wax rim to simulate the mandible. CBCT images were obtained using Cranex 3D and ProMax 3D CBCT systems with and without MAR algorithm before and after creation of defects. Two experienced radiologists observed the images twice with a 2-week interval. Data were analyzed using SPSS software version 22.The Kappa coefficient of agreement, the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy of different imaging modalities were calculated and analyzed. According to the kappa statistics, the intra- and inter-observer agreements were higher for images without the MAR algorithm compared with those with the MAR algorithm. In both CBCT systems, use of MAR algorithm decreased the area under the ROC curve and subsequently the diagnostic accuracy for detection of fenestration and dehiscence. The sensitivity, specificity and accuracy of both CBCT systems were higher in absence of the MAR algorithm. The specificity of ProMax 3D for detection of fenestration was equal with/without the MAR algorithm. Although CBCT is suitable for detection of peri-implant defects, application of the MAR algorithm does not enhance the detection of peri-implant fenestration and dehiscence.

scholarly journals Metal Artifact Reduction in Cone-Beam Computed Tomography for Head and Neck Radiotherapy

2016 ◽  
Vol 15 (6) ◽  
pp. NP88-NP94 ◽  
Author(s):  
Mark Korpics ◽  
Paul Johnson ◽  
Rakesh Patel ◽  
Murat Surucu ◽  
Mehee Choi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Head And Neck ◽  
Cone Beam Computed Tomography ◽  
Regions Of Interest ◽  
Cone Beam ◽  
Artifact Reduction ◽  
Metal Artifacts ◽  
Dental Fillings ◽  
Computed Tomography Images ◽  
Streak Artifacts

Purpose: To evaluate a method for reducing metal artifacts, arising from dental fillings, on cone-beam computed tomography images. Materials and Methods: A projection interpolation algorithm is applied to cone-beam computed tomography images containing metal artifacts from dental fillings. This technique involves identifying metal regions in individual cone-beam computed tomography projections and interpolating the surrounding values to remove the metal from the projection data. Axial cone-beam computed tomography images are then reconstructed, resulting in a reduction in the streak artifacts produced by the metal. Both phantom and patient imaging data are used to evaluate this technique. Results: The interpolation substitution technique successfully reduced metal artifacts in all cases. Corrected images had fewer or no streak artifacts compared to their noncorrected counterparts. Quantitatively, regions of interest containing the artifacts showed reduced variance in the corrected images versus the uncorrected images. Average pixel values in regions of interest around the metal object were also closer in value to nonmetal regions after artifact reduction. Artifact correction tended to perform better on patient images with less complex metal objects versus those with multiple large dental fillings. Conclusion: The interpolation substitution is potentially an efficient and effective technique for reducing metal artifacts caused by dental fillings on cone-beam computed tomography image. This technique may be effective in reducing such artifacts in patients with head and neck cancer receiving daily image-guided radiotherapy.

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