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

机译:乳腺X射线图像计算机辅助检测的2型模糊推理系统设计

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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,放射线医生广泛地使用乳房X线乳房X线摄影术检测癌症。医师在解释中使用的这种计算机辅助系统图像提高了医师识别出的肿块的成就。由基本图像处理和分类部分组成的计算机辅助检测系统的工作仍在进行中。在质量分类中广泛使用了诸如人工神经网络和支持向量机结构之类的不同方法。我们在开放式访问中的先前工作是通过使用统计分析和使用Matlab对这些属性,属性和1类模糊的派生值统计,在数据库中使用MIAS包含来自数据库的质量和图像处理技术上的免费乳房X线照片图像,并在二级获得三个纹理属性。设计了带有统计值推断系统的模糊工具箱。在这项研究中,使用统计方法计算用于类型1系统的每个属性数据集的数据集标准差。这些值用作类型2系统参数不确定性的足迹。将这些数据集和与每个带有2型模糊推理系统的直方图相关的数据集作为单独的软件进行处理。我们已经测试了我们的系统2型模糊推理系统比1型模糊推理系统取得了更大的成功。

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