| 基于分数阶微分的超声斑点去噪 |
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| 引用本文： | 邵党国,周婷,刘帆,易三莉,相艳,马磊. 基于分数阶微分的超声斑点去噪[J]. 传感器与微系统, 2017, 36(9). DOI: 10.13873/J.1000-9787(2017)09-0139-04 |
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| 作者姓名： | 邵党国 周婷 刘帆 易三莉 相艳 马磊 |
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| 作者单位： | 昆明理工大学信息工程与自动化学院,云南昆明,650500 |
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| 基金项目： | 国家自然科学基金资助项目，昆明理工大学省级人才培养项目 |
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| 摘 要： | 为了保留更多的纹理信息,构建了基于具有阻止扩散的梯度阈值k,和分数阶微分的阶数v平衡关系的分数偏微分方程的图像去噪模型,其有效结合了分数微积分理论和偏微分方程方法,并通过分数微分掩模算子实现了数值.超声体模信验和体内成像表明:基于分数阶微分的各向异性扩散方法可以提高组织的信噪比(SNR)和超声图像的质量.
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| 关 键 词： | 各向异性扩散 斑点去噪 分数阶微分 超声图像 |
Ultrasonic speckle denoising based on fractional order differentiation |
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| SHAO Dang-guo,ZHOU Ting,LIU Fan,YI San-li,XIANG Yan,MA Lei. Ultrasonic speckle denoising based on fractional order differentiation[J]. Transducer and Microsystem Technology, 2017, 36(9). DOI: 10.13873/J.1000-9787(2017)09-0139-04 |
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| Authors: | SHAO Dang-guo ZHOU Ting LIU Fan YI San-li XIANG Yan MA Lei |
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| Abstract: | In order to preserve more texture information,the image denoising model based on fractional partial differential equations with balance relation between gradient threshold which prevents diffusion k and order number of fractional order differentiation v is constructed by effective combination of fractional calculus theory and partial differential equations method,and numerical is achieved using fractional differential mask operator.Ultrasound phantom testing and in vivo imaging show that the proposed method can improve the quality of an ultrasound image in terms of tissue SNR. |
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| Keywords: | anisotropic diffusion speckle denoising fractional order differentiation ultrasound image |
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