2023, Volume 16, Issue 6, pp 862 – 867

Investigating the slice thickness effect on noise and diagnostic content of single-source multi-slice computerized axial tomography

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Corresponding Author: Nashwan Karkhi Abdulkareem Unit of Biophysics, Department of Basic Science, College of Medicine, Hawler Medical University, Erbil, Iraq Email: nashwan.karkhi@gmail.com

Abstract

High-quality and detailed CT scan images are crucial for accurate diagnosis. Factors such as image noise and slice thickness affect image quality. This study aimed to determine the optimal slice thickness that minimized image noise while maintaining sufficient diagnostic information using the single-source computed tomography head protocol. Single-source CT images were examined using the Linux Operating system Ge Revolution 64-slice CT scanner, and a combination of statical analysis and DICOM CT image analysis was employed. The single-source energy head CT protocol was used to investigate the effect of slice thickness on noise and visibility in images. Different values of slice thickness 0.625, 1.25, 2.5, 3.75, 5, 7.5, and 10 were prepared, and then quantitative analysis was performed. Thinner slice thickness decreased image noise, increased visibility, and improved detection. Therefore, the balance between changing the thickness of the slice with the diagnostic content and image noise must be considered. Maximum slice thickness enhances CT image detail and structure despite more noise. Based on the results, a slice thickness of 1.25mm was identified as the optimal choice for reducing image noise and achieving better and more accurate detection using the single-source computed tomography head protocol. The study revealed that image noise tends to increase with greater slice thickness according to the Linux operating system. These findings can serve as a valuable guide for quality control methods in CT centers, emphasizing the need to determine the appropriate slice thickness to ensure an accurate diagnosis.

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About this article

PMC ID: 10478658
PubMed ID: 37675166
DOI: 10.25122/jml-2022-0188

Article Publishing Date (print): 6 2023
Available Online: 

Journal information

ISSN Printing: 1844-122X
ISSN Online: 1844-3117
Journal Title: Journal of Medicine and Life

Copyright License: Open Access

This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.


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