Classification of mammography based on fractal features sequence
Yan Kang · Zhongguo yixue yingxiang jishu · 2012
Objective To describe the texture features of mass and implement the classification for breast mass and normal glands by texture analysis.Methods The texture features were described using fractal dimension.The detailed breast images were obtained by multi-level fractal features extraction methods of breast mass,and many features were extracted.The detectable rate,ROC curve and area under curve(AUC) were utilized to establish the fractal feature vector,and then breast images were classified using support vector machine(SVM) method.Results Sixty suspicious areas were extracted and classified,and the SVM cross-validation accuracy was 84.50%.Conclusion The breast image classification methods based on the fractal dimensions can classify the breast mass and normal gland,describe the texture features of mammograms efficiently,and improve the accuracy rate for mass detection.