Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver
Reconstruction kernel is one of the parameters that affects the computed tomography (CT) image quality. This study aimed to evaluate the effects of applying three different reconstruction kernels on image quality in 3-phased CT of the liver. A total of 63 CT liver images including normal liver (n...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2021
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| Online Access: | http://journalarticle.ukm.my/18824/ http://journalarticle.ukm.my/18824/1/145-150%2B%2B%2BMohd%2BHafizi%2BMahmud.pdf |
| _version_ | 1848814676465418240 |
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| author | Nur Amalina Ameruddin, Sulaiman Md Dom, Mohd Hafizi Mahmud, |
| author_facet | Nur Amalina Ameruddin, Sulaiman Md Dom, Mohd Hafizi Mahmud, |
| author_sort | Nur Amalina Ameruddin, |
| building | UKM Institutional Repository |
| collection | Online Access |
| description | Reconstruction kernel is one of the parameters that affects the computed tomography (CT) image quality. This study
aimed to evaluate the effects of applying three different reconstruction kernels on image quality in 3-phased CT of the
liver. A total of 63 CT liver images including normal liver (n = 43) and liver lesion (n = 20) were retrospectively reviewed.
Smooth (B20f), medium smooth (B30f) and medium (B40f) reconstruction kernels were employed in the image reconstruction
process. Mean attenuation, image noise, and signal-to-noise ratio (SNR) values from each kernel reconstruction were
quantified and compared among those kernels using One Way Analysis of Variance (ANOVA) statistical analysis. Significant
changes in image noise and SNR were observed in the normal liver (p < 0.001, respectively) following the application of
those reconstruction kernels. However, no significant changes in mean attenuation, image noise, and SNR were demonstrated
in the liver lesion (p > 0.05). Application of smooth (B20f), medium smooth (B30f), and medium (B40f) kernel
reconstructions would significantly affect the image noise and SNR in the normal liver of CT images instead of liver lesions.
Hence, proper selection of reconstruction kernel is important in CT images reconstruction to improve precision in diagnostic
CT interpretation. |
| first_indexed | 2025-11-15T00:37:52Z |
| format | Article |
| id | oai:generic.eprints.org:18824 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T00:37:52Z |
| publishDate | 2021 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org:188242022-06-24T00:58:17Z http://journalarticle.ukm.my/18824/ Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver Nur Amalina Ameruddin, Sulaiman Md Dom, Mohd Hafizi Mahmud, Reconstruction kernel is one of the parameters that affects the computed tomography (CT) image quality. This study aimed to evaluate the effects of applying three different reconstruction kernels on image quality in 3-phased CT of the liver. A total of 63 CT liver images including normal liver (n = 43) and liver lesion (n = 20) were retrospectively reviewed. Smooth (B20f), medium smooth (B30f) and medium (B40f) reconstruction kernels were employed in the image reconstruction process. Mean attenuation, image noise, and signal-to-noise ratio (SNR) values from each kernel reconstruction were quantified and compared among those kernels using One Way Analysis of Variance (ANOVA) statistical analysis. Significant changes in image noise and SNR were observed in the normal liver (p < 0.001, respectively) following the application of those reconstruction kernels. However, no significant changes in mean attenuation, image noise, and SNR were demonstrated in the liver lesion (p > 0.05). Application of smooth (B20f), medium smooth (B30f), and medium (B40f) kernel reconstructions would significantly affect the image noise and SNR in the normal liver of CT images instead of liver lesions. Hence, proper selection of reconstruction kernel is important in CT images reconstruction to improve precision in diagnostic CT interpretation. Penerbit Universiti Kebangsaan Malaysia 2021 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/18824/1/145-150%2B%2B%2BMohd%2BHafizi%2BMahmud.pdf Nur Amalina Ameruddin, and Sulaiman Md Dom, and Mohd Hafizi Mahmud, (2021) Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver. Malaysian Applied Biology, 50 (2). pp. 145-150. ISSN 0126-8643 https://jms.mabjournal.com/index.php/mab/issue/view/36 |
| spellingShingle | Nur Amalina Ameruddin, Sulaiman Md Dom, Mohd Hafizi Mahmud, Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title | Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title_full | Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title_fullStr | Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title_full_unstemmed | Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title_short | Effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase CT of liver |
| title_sort | effects of smooth, medium smooth and medium reconstruction kernels on image quality in three-phase ct of liver |
| url | http://journalarticle.ukm.my/18824/ http://journalarticle.ukm.my/18824/ http://journalarticle.ukm.my/18824/1/145-150%2B%2B%2BMohd%2BHafizi%2BMahmud.pdf |