SU-E-I-35: Development of Stand-Alone Filtered Backprojection and Iterative Reconstruction Methods Using the Raw CT Data Exported From Clinical Lung Screening Scans

2015 ◽  
Vol 42 (6Part6) ◽  
pp. 3249-3249 ◽  
Author(s):  
S Young ◽  
J Hoffman ◽  
F Noo ◽  
M McNitt-Gray
2019 ◽  
Vol 46 (12) ◽  
Author(s):  
Viktor Haase ◽  
Katharina Hahn ◽  
Harald Schöndube ◽  
Karl Stierstorfer ◽  
Andreas Maier ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-14
Author(s):  
Joshua Kim ◽  
Huaiqun Guan ◽  
David Gersten ◽  
Tiezhi Zhang

Tetrahedron beam computed tomography (TBCT) performs volumetric imaging using a stack of fan beams generated by a multiple pixel X-ray source. While the TBCT system was designed to overcome the scatter and detector issues faced by cone beam computed tomography (CBCT), it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction algorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and that algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper, the SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data and data acquired using the TBCT benchtop system. The modified SART reconstruction algorithms were able to mitigate the effects of using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due to either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for dual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view.


Author(s):  
B. M. W. Tsui ◽  
G. T. Gullberg ◽  
H. B. Hu ◽  
J. G. Ballard ◽  
D. R. Gilland ◽  
...  

2017 ◽  
Vol 59 (5) ◽  
pp. 553-559 ◽  
Author(s):  
Yun Hye Ju ◽  
Geewon Lee ◽  
Ji Won Lee ◽  
Seung Baek Hong ◽  
Young Ju Suh ◽  
...  

Background Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal–Wallis test and the Chi-square test. Results Effective doses were 61–87% lower in groups 2–5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups ( P < 0.001). Overall image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1–3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1–4, but were significantly poorer in group 5. Conclusion Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.


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