Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.
Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification.
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DOI：
10.1016/j.ultrasmedbio.2020.08.009
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发表时间：
2020-12
影响因子：
2.9
通讯作者：
Parker, Kevin J.
中科院分区：
文献类型：
--
作者：
Baek, Jihye;Poul, Sedigheh S.;Swanson, Terri A.;Tuthill, Theresa;Parker, Kevin J.
关键词：
五十年来对组织背向散射性质的研究已经产生了许多有前途的诊断参数。我们最近介绍了两个与超声散射的生物物理学直接相关的分析；基于匹配滤波方法的h扫描用于区分散射传递函数，以及用于量化散斑图案的毛刺分布。总之，这些分析可以产生至少五个参数，这些参数与组织中的超声波数学直接相关。在35只大鼠的肝脏中，在正常条件下和暴露于以不同组合诱导炎症、纤维化和脂肪变性的化合物后，测量了这些指标。一种分类技术，支持向量机，被用来确定五个参数的聚类，这些参数是不同肝脏状况的特征。通过多参数测量方法和聚类的确定，区分不同类型的肝脏病理，准确率为94.6%。
Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering; the H-scan based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds which induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy.
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影响因子：
2.9
作者：
Al-Kadi, Omar S.;Chung, Daniel Y. F.;Noble, J. Alison
通讯作者：
Noble, J. Alison
影响因子：
2.4
作者：
CAMPBELL, JA;WAAG, RC
通讯作者：
WAAG, RC
影响因子：
1.4
作者：
Parker KJ;Baek J
通讯作者：
Baek J
影响因子：
4.6
作者：
Liao, Yin-Yin;Yang, Kuen-Cheh;Yeh, Chih-Kuang
通讯作者：
Yeh, Chih-Kuang
影响因子：
2.1
作者：
Parker, Kevin J.;Carroll-Nellenback, Jonathan J.;Wood, Ronald W.
通讯作者：
Wood, Ronald W.