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Type-2 fuzzy inference system design for computer aided detection in mammogram image

机译:乳房X线图图像计算机辅助检测Type-2模糊推理系统设计

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Nowadays the detection of cancer of the breast mass X-ray mammography is widely used by radiologists. This computer-aided system images used by physicians in the interpretation raises the accomplishments of physicians identified masses. Work on computer-aided detection systems consisting of basic image processing and classification section is still in progress. Different methods such as artificial neural networks and support vector machine structure is widely used in mass classification. Previous work in our open access has MIAS containing mass from the database and free mammogram images on image processing techniques and three texture attribute in the second degree by using statistical analysis and derived value statistics of these attributes, attributes, and type-1 fuzzy using Matlab fuzzy toolbox with statistical values inference system is designed. In this study, the standard deviation of the data set using a statistical method on each attribute data set used for type-1 system is calculated. These values are used as the footprint of the uncertainty of the type-2 system parameters. These data sets and data sets related to each piece of histogram chart with type-2 fuzzy inference system was conducted as separate software. We have tested our system type-2 fuzzy inference system has produced more successful than type-1 fuzzy inference system.
机译:如今,乳房质量X射线乳腺X线摄影癌症的检测被放射科学家广泛使用。医师在解释中使用的计算机辅助系统图像提出了医师所确定的群众的成就。在计算机辅助检测系统上工作,包括基本图像处理和分类部分仍在进行中。不同的方法,如人工神经网络和支持向量机结构广泛用于质量分类。我们的开放访问中的先前工作具有偏眉,通过使用Matlab使用统计分析和派生价值统计数据库处理技术和三个纹理属性在图像处理技术和三个纹理属性中的偏眉像设计了具有统计值推理系统的模糊工具箱。在本研究中,计算使用用于类型-1系统的每个属性数据集的统计方法的数据集的标准偏差。这些值被用作2型系统参数的不确定性的占用空间。这些数据集和与具有类型模糊推理系统的每条直方图图表相关的数据集和数据集被称为单独的软件。我们已经测试了我们的系统类型-2模糊推理系统,该系统生产比1型模糊推理系统更成功。

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