An Improved Method of Automated Noise Measurement System in CT Images.
Algorithms
Automated Noise Calculation
Computed Tomography
Image Processing, Computer-Assisted
Image Quality
Ionizing Radiation
X-Rays
Journal
Journal of biomedical physics & engineering
ISSN: 2251-7200
Titre abrégé: J Biomed Phys Eng
Pays: Iran
ID NLM: 101589641
Informations de publication
Date de publication:
Apr 2021
Apr 2021
Historique:
received:
10
06
2019
accepted:
04
08
2019
entrez:
3
5
2021
pubmed:
4
5
2021
medline:
4
5
2021
Statut:
epublish
Résumé
It is necessary to have an automated noise measurement system working accurately to optimize dose in computerized tomography (CT) examinations. This study aims to develop an algorithm to automate noise measurement that can be implemented in CT images of all body regions. In this retrospective study, our automated noise measurement method consists of three steps as follows: the first is segmenting the image of the patient. The second is developing a standard deviation (SD) map by calculating the SD value for each pixel with a sliding window operation. The third step is estimating the noise as the smallest SD from the SD map. The proposed method was applied to the images of a homogenous phantom and a full body adult anthropomorphic phantom, and retrospectively applied to 27 abdominal images of patients. For a homogeneous phantom, the noises calculated using our proposed and previous algorithms have a linear correlation with R An automated noise calculation has been proposed and successfully implemented in all body regions. It is not only accurate and easy to implement but also not influenced by the subjectivity of user.
Sections du résumé
BACKGROUND
BACKGROUND
It is necessary to have an automated noise measurement system working accurately to optimize dose in computerized tomography (CT) examinations.
OBJECTIVE
OBJECTIVE
This study aims to develop an algorithm to automate noise measurement that can be implemented in CT images of all body regions.
MATERIALS AND METHODS
METHODS
In this retrospective study, our automated noise measurement method consists of three steps as follows: the first is segmenting the image of the patient. The second is developing a standard deviation (SD) map by calculating the SD value for each pixel with a sliding window operation. The third step is estimating the noise as the smallest SD from the SD map. The proposed method was applied to the images of a homogenous phantom and a full body adult anthropomorphic phantom, and retrospectively applied to 27 abdominal images of patients.
RESULTS
RESULTS
For a homogeneous phantom, the noises calculated using our proposed and previous algorithms have a linear correlation with R
CONCLUSION
CONCLUSIONS
An automated noise calculation has been proposed and successfully implemented in all body regions. It is not only accurate and easy to implement but also not influenced by the subjectivity of user.
Identifiants
pubmed: 33937124
doi: 10.31661/jbpe.v0i0.1198
pii: JBPE-11-2
pmc: PMC8064134
doi:
Types de publication
Journal Article
Langues
eng
Pagination
163-174Informations de copyright
Copyright: © Journal of Biomedical Physics and Engineering.
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