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首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Classification of ultrasonic B mode images of the breast using frequency diversity and Nakagami statistics
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Classification of ultrasonic B mode images of the breast using frequency diversity and Nakagami statistics

机译：使用频率分集和Nakagami统计数据对乳房B超图像进行分类

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摘要

The parameters of the Nakagami distribution have been utilized in the past to classify lesions in breast tissue as benign or malignant. To avoid the effect of operator-gain settings on the parameters of the Nakagami distribution, normalized parameters were utilized for the classification. The normalized parameter was defined as the ratio of the parameter at the site of the lesion to its average value over several regions away from the site. This technique, however, was very time consuming. In this paper, the application of frequency diversity and compounding is explored to achieve this normalization. Lesions are classified using these normalized parameters at the site. A receiver operating characteristic (ROC) analysis of the parameters of the Nakagami distribution has been conducted before and after compounding on a data set of 60 benign and 65 malignant lesions. The ROC results indicate that this technique can reasonably classify lesions in breast tissue as benign or malignant.
机译：过去已经使用Nakagami分布的参数将乳腺组织中的病变分类为良性或恶性。为了避免操作员增益设置对Nakagami分布的参数产生影响，将归一化参数用于分类。归一化参数定义为病变部位的参数与其在远离部位的几个区域上的平均值之比。但是，该技术非常耗时。在本文中，探索了频率分集和复合的应用以实现这种归一化。在这些部位使用这些标准化参数对病变进行分类。在对60例良性和65例恶性病变的数据集进行混合之前和之后，已经对Nakagami分布的参数进行了接收器操作特征（ROC）分析。 ROC结果表明，该技术可以合理地将乳腺组织中的病变分类为良性或恶性。

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