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Flow Artifact Removal in Carotid Wall Imaging Based on Black and Gray-Blood Dual-Contrast Images Subtraction

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机构: [1]Peking Univ, Acad Adv Interdisciplinary Studies, Beijing, Peoples R China; [2]Peking Univ, Coll Engn, Yiheyuan Rd 5, Beijing 100871, Peoples R China; [3]Capital Med Univ, Beijing Anzhen Hosp, Dept Radiol, Beijing, Peoples R China
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关键词: blood signal suppression flow artifact removal black blood DCIS carotid MRI vessel wall imaging

摘要:
Purpose: To develop and validate a dual-contrast image subtraction (DCIS) strategy for eliminating the flow artifacts in black-blood carotid MRI. Methods: Twelve patients with carotid stenosis and eight healthy volunteers were imaged using the black and grayblood dual-contrast imaging based on the relaxationenhanced compressed sensing three-dimensional motion-sensitizing driven equilibrium prepared rapid-gradient-echo (RECS-3D MERGE) sequence. Subtraction of black-blood images (BBIs) and gray-blood images (GBIs), together with a preweighting procedure, was performed to eliminate the residual blood signal in BBIs. A wavelet denoising procedure was applied to offset the noise amplification. In addition to the lumen signal-to-noise ratio (SNR) and wall-lumen contrast-tonoise ratio (CNR), the signal variance ratio (SVR) and contrast variance ratio (CVR) were also used to evaluate the blood suppression efficiency. Results: By choosing the weighting factor of one, the lumen SNR of DCIS images was approximately 1% of that of the original BBIs, and the CNR showed a 91.4% improvement as compared with the BBIs. The median of the lumen SVR decreased to zero, and the CVR increased to 123% of that of the BBIs. Conclusions: DCIS is demonstrated to be an effective strategy for sufficiently removing the residual flow signal from black-blood carotid MRI. (C) 2016 International Society for Magnetic Resonance in Medicine

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出版当年[2016]版:
大类 | 2 区 医学
小类 | 2 区 核医学
最新[2023]版:
大类 | 3 区 医学
小类 | 3 区 核医学
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出版当年[2015]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
最新[2023]版:
Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2015版] 出版当年五年平均 出版前一年[2014版] 出版后一年[2016版]

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第一作者机构: [1]Peking Univ, Acad Adv Interdisciplinary Studies, Beijing, Peoples R China;
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通讯机构: [1]Peking Univ, Acad Adv Interdisciplinary Studies, Beijing, Peoples R China; [2]Peking Univ, Coll Engn, Yiheyuan Rd 5, Beijing 100871, Peoples R China;
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