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分维方法在肝癌超声图像纹理识别中的性能比较研究
引用本文:季桂树,江乐新,禹智夫.分维方法在肝癌超声图像纹理识别中的性能比较研究[J].中南大学学报(自然科学版),2011(9).
作者姓名:季桂树  江乐新  禹智夫
作者单位:中南大学地球科学与信息物理学院;中南大学信息科学与工程学院;中南大学机电工程学院;长沙市第八医院超声科;
摘    要:研究描述超声肝图像纹理特征的分维方法。用14幅正常肝样本图像和14幅原发性肝癌样本图像检验并比较评估4种分维方法。用布朗运动方法、毯子法、傅里叶功率谱法和差分盒计数法4种方法得到的分维作为特征进行ROC(Receiver operating characteristic)分析,以SVM作为模式分类方法的分类正确率进行分析。研究结果表明:除了分数布朗运动方法外,由毯子法、傅里叶功率谱法和差分盒计数法获得的描述正常肝图像感兴趣区域的分维值明显小于描述原发性癌图像感兴趣区域的分维值;采用傅里叶功率谱方法得到最大的ROC曲线下的面积;用SVM(Support vector machine)方法进行分类也取得了与ROC分析类似的结果,即用傅里叶功率谱方法进行分类准确度最高,分数布朗运动和差分盒计数方法效果较差,毯子方法效果居中;傅里叶功率谱方法是描述超声肝图像纹理特征最适合的方法。

关 键 词:超声肝图像  分维方法  傅里叶功率谱  纹理特征  ROC分析  SVM  

Performance comparison of fractal dimension analysis methods in differentiating normal liver and primary liver cancer image
JI Gui-shu,JIANG Le-xin,YU Zhi-fu.Performance comparison of fractal dimension analysis methods in differentiating normal liver and primary liver cancer image[J].Journal of Central South University:Science and Technology,2011(9).
Authors:JI Gui-shu    JIANG Le-xin  YU Zhi-fu
Institution:JI Gui-shu1,2,JIANG Le-xin3,YU Zhi-fu4 (1.School of Geomatics and Info-physics,Central South University,Changsha 410083,China,2.School of Information Science and Engineering,3.School of Mechanical and Electrical Engineering,4.Ultrasound Section,Changsha City Eighth Hospital,Changsha 410100,China)
Abstract:A detailed study of fractal-based methods for texture characterization of normal ultrasonic liver parenchyma and primary liver cancer image was made.The 4 types of methods of fractal dimension estimation for the texture feature characterization of normal liver and primary liver cancer image were tested and compared and evaluated based on 14 normal liver and 14 primary liver cancer sample images.ROC was used as an analysis method and SVM was used as a pattern classification method for the performance evaluat...
Keywords:ultrasonic liver image  fractal dimension method  Fourier power spectrum  texture feature  ROC analysis  SVM  
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