2017
DOI: 10.1016/j.ejmp.2017.02.009
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Simulation of scanner- and patient-specific low-dose CT imaging from existing CT images

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Cited by 10 publications
(4 citation statements)
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References 34 publications
(47 reference statements)
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“…The major number of investigations are retrospective studies, where the amount of radiation exposure reduction cannot be generalized because of the missing ground truth. However, when comparing our study to the work of others, which used simulation tools (24)(25)(26), our results suffer from a 5-s delay between the two consecutive scans. As a result, we observe a difference in contrast due to the physiology in liver lesions.…”
Section: Discussionmentioning
confidence: 78%
“…The major number of investigations are retrospective studies, where the amount of radiation exposure reduction cannot be generalized because of the missing ground truth. However, when comparing our study to the work of others, which used simulation tools (24)(25)(26), our results suffer from a 5-s delay between the two consecutive scans. As a result, we observe a difference in contrast due to the physiology in liver lesions.…”
Section: Discussionmentioning
confidence: 78%
“… 76 , 77 Thus various groups have proposed low-dose simulations using reconstructed CT images. The methods involve adding Gaussian 76 , 77 or a combination of Gaussian and Poisson noise 78 on the sinogram of the forward projection of the CT image. Although there has been limited validation of the appearance of lung nodules against simulated low dose simulation, 79 there has been no validation on the efficacy of these methods on the appearance of airways.…”
Section: Discussionmentioning
confidence: 99%
“…However, nonlocal noise properties in reconstructed CT images (Massoumzadeh et al 2009) make it very difficult to simulate noise directly in the image domain. In the absence of raw projection data, an alternative way can be to generate a virtual sinogram from a high-dose CT image (Naziroglu et al 2017, Takenaga et al 2016 and model dose reduction in the sinogram domain.…”
Section: Introductionmentioning
confidence: 99%