Optimization of image quality of non-contrast urography CT tracking with the selection of the right iDose4 level iterative reconstruction technique

Authors

  • Muhamad Faik Universitas 'Aisyiyah Yogyakarta

DOI:

https://doi.org/10.31101/ijhst.v4i3.2798
Abstract views 171 times

Keywords:

image quality, CT urography non-contrast, FBP, iDose4

Abstract

Optimal urinary tract image and able to identify differences in urinary tract image information on urography CT is urography CT tracking image with a thin slice thickness parameter of 1 mm (Sulaksono et al., 2016). However, the thinner the slice thickness will produce high noise that can affect the diagnosis. The FBP algorithm, the standard algorithm for image reconstruction on CT scans, produces streak artifacts and significantly increases image noise when the radiation dose is reduced tremendously (Willemink, de Jong et al., 2013; Willemink, Leiner et al., 2013). Iterative reconstruction iDose4 is a fourth-generation image reconstruction technique that can significantly improve image quality, noise reduction, and radiation dose reduction. This study aims to determine the difference in noise values and diagnostic information of non-contrast urography CT tracking images with variations in FBP and iDose four reconstruction techniques. This type of research is experimental research. Data collection began in May 2022 to June 2022 at the Radiology Installation of RSUD Salatiga City. The results showed that selecting iDose4 level 6 iterative reconstruction techniques produced the best image quality and diagnostic information on coronal tracking images of urinary tract CT non-contrast urography. Therefore, the iDose4 level 6 iterative reconstruction technique should be used as a standard protocol for conducting non-contrast urography CT examinations.

References

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Published

2023-04-17

How to Cite

Faik, M. (2023). Optimization of image quality of non-contrast urography CT tracking with the selection of the right iDose4 level iterative reconstruction technique. International Journal of Health Science and Technology, 4(3), 255–266. https://doi.org/10.31101/ijhst.v4i3.2798

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