Liver tissue characterization for each pixel in ultrasound image using multi-Rayleigh model
Liver tissue characterization for each pixel in ultrasound image using multi-Rayleigh model
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DOI：
10.7567/jjap.53.07kf27
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发表时间：
2014-07-01
影响因子：
1.5
通讯作者：
Hachiya, Hiroyuki
中科院分区：
文献类型：
--
作者：
Higuchi, Tatsuya;Hirata, Shinnosuke;Hachiya, Hiroyuki
在前期的研究中，我们提出了多瑞利模型作为肝纤维化的幅度分布模型，并成功地对感兴趣区域的肝纤维化进行了定量评价。为了更准确地评估肝纤维化，本文使用多瑞利模型将临床回波图像中每个像素的幅度转换为低回声和纤维化概率。分析了肝纤维化的临床声像图，并讨论了这些概率与肝纤维化分期的关系。我们还表明，纤维化组织的信息可以更准确地提取使用纤维化概率比使用传统的方法的基础上的恒虚警率（CFAR）处理。我们的结论是，所提出的方法是有效的定量诊断肝纤维化。(C)2014日本应用物理学会
In our previous study, we proposed the multi-Rayleigh model as an amplitude distribution model of fibrotic liver, and succeeded in the quantitative evaluation of liver fibrosis in the region of interest. In this paper, to evaluate liver fibrosis more accurately, the amplitude of each pixel in a clinical echo image was converted to hypoechoic and fibrotic probabilities using the multi-Rayleigh model. Clinical echo images of liver fibrosis were analyzed and the relationship between these probabilities and the stage of liver fibrosis were discussed. We also showed that the information on fibrotic tissue can be extracted more accurately using the fibrotic probability than using the conventional method based on the constant false alarm rate (CFAR) processing. We conclude that the proposed method is valid for the quantitative diagnosis of liver fibrosis. (C) 2014 The Japan Society of Applied Physics