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http://dx.doi.org/10.7742/jksr.2019.13.1.111

Truncation Artifact Reduction Using Weighted Normalization Method in Prototype R/F Chest Digital Tomosynthesis (CDT) System  

Son, Junyoung (Department of Radiation Convergence Engineering, Yonsei University)
Choi, Sunghoon (Department of Radiological Science, Yonsei University)
Lee, Donghoon (Department of Radiation Convergence Engineering, Yonsei University)
Kim, Hee-Joung (Department of Radiation Convergence Engineering, Yonsei University)
Publication Information
Journal of the Korean Society of Radiology / v.13, no.1, 2019 , pp. 111-118 More about this Journal
Abstract
Chest digital tomosynthesis has become a practical imaging modality because it can solve the problem of anatomy overlapping in conventional chest radiography. However, because of both limited scan angle and finite-size detector, a portion of chest cannot be represented in some or all of the projection. These bring a discontinuity in intensity across the field of view boundaries in the reconstructed slices, which we refer to as the truncation artifacts. The purpose of this study was to reduce truncation artifacts using a weighted normalization approach and to investigate the performance of this approach for our prototype chest digital tomosynthesis system. The system source-to-image distance was 1100 mm, and the center of rotation of X-ray source was located on 100 mm above the detector surface. After obtaining 41 projection views with ${\pm}20^{\circ}$ degrees, tomosynthesis slices were reconstructed with the filtered back projection algorithm. For quantitative evaluation, peak signal to noise ratio and structure similarity index values were evaluated after reconstructing reference image using simulation, and mean value of specific direction values was evaluated using real data. Simulation results showed that the peak signal to noise ratio and structure similarity index was improved respectively. In the case of the experimental results showed that the effect of artifact in the mean value of specific direction of the reconstructed image was reduced. In conclusion, the weighted normalization method improves the quality of image by reducing truncation artifacts. These results suggested that weighted normalization method could improve the image quality of chest digital tomosynthesis.
Keywords
Truncation artifact; Chest digital tomosynthesis; Filtered back projection; Weighted normalization;
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