Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on c...

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Main Authors: Chan-Rok Park, Seong-Hyeon Kang, Young-Jin Lee
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/11/2/319
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author Chan-Rok Park
Seong-Hyeon Kang
Young-Jin Lee
author_facet Chan-Rok Park
Seong-Hyeon Kang
Young-Jin Lee
author_sort Chan-Rok Park
collection DOAJ
description Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-AC<sub>Dixon-CAIPI</sub>) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-AC<sub>Dixon-GRAPPA</sub>) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting <sup>18</sup>F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-AC<sub>Dixon-CAIPI</sub> PET image was better than that of the MR-AC<sub>Dixon-GRAPPA</sub> PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.
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spelling doaj.art-55cbb3be2e094323b3aa2af66214a2b92023-12-11T17:16:44ZengMDPI AGDiagnostics2075-44182021-02-0111231910.3390/diagnostics11020319Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom StudyChan-Rok Park0Seong-Hyeon Kang1Young-Jin Lee2Department of Radiological Science, Jeonju University, 303, Cheonjam-ro, Wansan-gu, Jeonju-si, Jeollabuk-do 55069, KoreaDepartment of Radiological Science, Gachon University, 191, Hambakmoero, Yeonsu-gu, Incheon 21936, KoreaDepartment of Radiological Science, Gachon University, 191, Hambakmoero, Yeonsu-gu, Incheon 21936, KoreaRecently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-AC<sub>Dixon-CAIPI</sub>) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-AC<sub>Dixon-GRAPPA</sub>) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting <sup>18</sup>F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-AC<sub>Dixon-CAIPI</sub> PET image was better than that of the MR-AC<sub>Dixon-GRAPPA</sub> PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.https://www.mdpi.com/2075-4418/11/2/319positron emission tomography (PET)/magnetic resonance (MR)total variation (TV)noise-reduction algorithmattenuation correctionnuclear medicine
spellingShingle Chan-Rok Park
Seong-Hyeon Kang
Young-Jin Lee
Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
Diagnostics
positron emission tomography (PET)/magnetic resonance (MR)
total variation (TV)
noise-reduction algorithm
attenuation correction
nuclear medicine
title Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
title_full Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
title_fullStr Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
title_full_unstemmed Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
title_short Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study
title_sort feasibility of total variation noise reduction algorithm according to various mr based pet images in a simultaneous pet mr system a phantom study
topic positron emission tomography (PET)/magnetic resonance (MR)
total variation (TV)
noise-reduction algorithm
attenuation correction
nuclear medicine
url https://www.mdpi.com/2075-4418/11/2/319
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AT youngjinlee feasibilityoftotalvariationnoisereductionalgorithmaccordingtovariousmrbasedpetimagesinasimultaneouspetmrsystemaphantomstudy