Abstract
<h3>Background</h3> The first generation stationary intraoral tomosynthesis (sIOT) device, developed at University of North Carolina (UNC), provides 3-D information in intraoral imaging with a speed and dose comparable with those of traditional intraoral radiography. Initial research shows promise in several diagnostic tasks, including caries and fracture detection. However, the original iterative reconstruction produces artifacts adjacent to metal restorations. Two new iterative reconstructions with metal artifact reduction (MAR1 and MAR2) have been developed. MAR1 segments the metal out before reconstruction and adds it back after reconstruction. MAR2 minimizes the artifact amplified at each iteration by dividing the projected error by the number of slices. <h3>Objective(s)</h3> The aim of this study was to compare the effectiveness of metal artifact reduction in tomosynthesis. <h3>Study Design</h3> Pilot samples of 2 extracted premolars with amalgam restorations were imaged by using the sIOT system. Reconstructions were generated using the original, MAR1, and MAR2 algorithms. Using line density plots, artifact pixel intensity and artifact width were measured for the original, MAR1, and MAR2 algorithms. <h3>Results</h3> The difference between average dentin pixel intensity and artifact pixel intensity for sample 1 was 8016, –5781, and 759 for the original, MAR1, and MAR2 reconstructions, respectively. Artifact width was 2.61 mm, 0.82 mm, and 1.38 mm, respectively. For sample 2, the difference in intensity was 8248, –5399, and 93, respectively. Artifact width was 1.71 mm, 1.06 mm, and 0.81 mm, respectively. <h3>Discussion/Conclusions</h3> MAR1 and MAR2 reduced the intensity of the artifacts; however, reduction by MAR2 was more pronounced. MAR1 produced radiopaque artifacts, whereas MAR2 produced radiolucent artifacts. MAR1 and MAR2 reduced the width of the artifacts, but the extent was reversed between the samples. The results support the value of MAR for tomosynthesis and suggests that MAR2 may be more effective. Continued development of artifact reduction techniques is needed with a more in-depth study using a larger sample size.
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