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Morphologic and texture features in classifying the malignant and benign breast nodules in ultrasonography

Morphologic and texture features in classifying the malignant and benign breast nodules in ultrasonography
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摘要 Objective To develop a computer-aided diagnosis(CAD)system with automatic contouring and morphologic and textural analysis to aid on the classification of breast nodules on ultrasound images.Methods A modified Level Set method was proposed to automatically segment the breast nodules(46malignant and 60benign nodules).Following,16morphologic features and 17texture features from the extracted contour were calculated and principal component analysis(PCA)was applied to find the optimal feature vector dimensions.Fuzzy C-means classifier was utilized to identify the breast nodule as benign or malignant with selected principal vectors.Results The performance of morphologic features was 78.30%for accuracy,67.39%for sensitivity and 86.67%for specificity,while the latter was 72.64%,58.70%and 83.33%,respectively.After the combination of the two features,the result was exactly the same with the morphologic performance.Conclusion This system performs well in classifying the malignant breast nodule from the benign breast nodule. Objective To develop a computer-aided diagnosis（CAD）system with automatic contouring and morphologic and tex-tural analysis to aid on the classification of breast nodules on ultrasound images .Methods A modified Level Set method was pro-posed to automatically segment the breast nodules（46 malignant and 60 benign nodules） .Following ,16 morphologic features and 17 texture features from the extracted contour were calculated and principal component analysis（PCA）was applied to find the optimal feature vector dimensions .Fuzzy C-means classifier was utilized to identify the breast nodule as benign or malignant with selected principal vectors .Results The performance of morphologic features was 78 .30% for accuracy ,67 .39% for sensitivity and 86 .67%for specificity ,while the latter was 72 .64% ,58 .70% and 83 .33% ,respectively .After the combination of the two features ,the re-sult was exactly the same with the morphologic performance .Conclusion This system performs well in classifying the malignant breast nodule from the benign breast nodule .
作者 陈秋霞 Xiang Jun Liu Qi Liu Jian
机构地区 Department of Equipment College of Electrical Engineering and Information
出处 《重庆医学》 CAS CSCD 北大核心 2014年第30期4046-4049,共4页 Chongqing medicine
基金 西华大学四川省信号与信息处理重实实验室基金项目(SGXZD0101-10-1)
关键词 computer-aided diagnosis breast neoplasms morphologic feature texture feature computer-aided diagnosis breast neoplasms morphologic feature texture feature
分类号 R737.9 [医药卫生—肿瘤]
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参考文献13

  • 1Joo S, Yang YS, Moon WK,et al. Computer-aided diagno- sis of solid breast nodules:use of an artificial neural net- work based on multiple sonographie features[J]. IEEE Trans Med Imaging, 2004,23 (10): 1292-1230.
  • 2Kim KG, Kim JH, Min BG. Classification of malignant and benign nodules using boundary characteristics in breast ultrasonogramsment[J]. J Digit Imaging, 2002,15 Suppl 1: 224-227.
  • 3Huang YL, Lin SH, Chen DR. Computer-aided diagnosis applied to 3-D US of solid breast nodules by using princi- pal component analysis and image retrieval[J]. Conf Proc IEEE Eng Med Biol Soc, 2005,2 : 1802-1805.
  • 4Li CM,Xu CY,Gui CF,et al. Level set evolution without re-initialization: a new variational formulation[J]. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit, 2005,1 : 430-436.
  • 5Nie K, Chen JH, Yu H J, et al. Quantitative analysis of le- sion morphology and texture features for diagnostic pre diction in breast MRI [J]. Acad Radiol, 2008, 15 ( 12 ) : 1513-1525.
  • 6Guliato D, Rangayyan RM, Carvalho JD, et al. Polygonal modeling of contours of breast nodules with the preserva- tion of spicules[J]. IEEE Trans Biomed Eng, 2008, 55 (1) :14-20.
  • 7Tsui PH, Liao YY,Chang CC, et al. Classification of be- nign and malignant breast nodules by 2-D analysis based on contour description and scatterer characterization[J]. IEEE Trans Med Imaging,2010,29(2) :513-522.
  • 8Yang W,Zhang S,Chen Y,et al. Shape symmetry analysis of breast nodules on ultrasound images[J]. Comput Biol Med,2009,39(3) :231-238.
  • 9Chen CY,Chiou H J, Chou SY, et al. Computer-aided diag nosis of soft-tissue nodules using sonographic morpholog ic and texture features[J]. Acad Radiol, 2009,16 (12): 1531-1538.
  • 10Huang YL, Chen DR,Jiang YR, et al. Computer-aided diag- nosis using morphological features for claasifying breast le- sions on ultrasound[J]. Ultrasound Obstet Gynecol, 2008,32 (4) :565-572.
重庆医学
2014年 第30期

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