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Ultrasonic liver tissues classification by fractal feature vector based on M-band wavelet transform

机译:基于M波段小波变换的超声肝组织分类分形特征向量

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This paper proposes a new fractal feature vector based on M-band wavelet transform for classification of ultrasonic liver images-normal liver, cirrhosis, and hepatoma. Classifications for liver images have revealed that the fractal feature vector is trustworthy. A hierarchical classifier produces 97.27% correct classification for the distinction of normal and abnormal liver image and 93.6% correct classification for the distinction of cirrhosis and hepatoma liver image.
机译:本文提出了一种基于M带小波变换的新分形特征向量,用于超声肝图像正常肝,肝硬化和肝癌的分类。肝脏图像的分类揭示了分形特征向量是值得信赖的。分层分类器产生97.27%的正确分类,以区分正常和异常的肝脏图像和93.6%的正确分类,以区分肝硬化和肝癌肝脏图像。

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