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篇名
Analyses of statistical feature fusion techniques in breast cancer detection
並列篇名
Analyses of statistical feature fusion techniques in breast cancer detection
作者 Sasikala Shanmugam (Sasikala Shanmugam)Arun Kumar Shanmugam (Arun Kumar Shanmugam)Bharathi Mayilswamy (Bharathi Mayilswamy)Ezhilarasi Muthusamy (Ezhilarasi Muthusamy)
中文摘要
Breast cancer is one of the mortal diseases amongst women with increased incidences and mortality rate in every year globally. As its symptoms are not prominently noticeable in early stage, the early detection is difficult. Over the past four decades Mammography is used for diagnosing breast diseases. Most of CAD systems use either Cranio-Caudal or Medio-Lateral Oblique mammographic views. Radiologist will look at both the view for better diagnosis. To incorporate this perception with CAD, the detection performance of various statistical feature fusion in fusing the texture features of these two mammographic views are analysed in this work. The improved performance of accuracy: 97.5%, sensitivity: 100%, specificity: 97.2%, precision: 97.1%, F1 score: 96.23%, Mathews Correlation Coefficient: 0.952% and Balanced Classification Rate: 98.74% was achieved with Local Binary Pattern features fused through Canonical Correlation Analysis.
起訖頁 311-316
關鍵詞 Breast cancer Mammogram MLO CC PCA CCA GDA DCA SVM
刊名 國際應用科學與工程學刊  
期數 202009 (17:3期)
出版單位 朝陽科技大學理工學院
該期刊-上一篇 A two stage converging genetic algorithm for graph clustering
 

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