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Detection of Architectural Distortion in Mammograms Acquired Prior to the Detection of Breast Cancer using Texture and Fractal Analysis

机译:用纹理和分形分析检测在乳腺癌检测之前获得的乳房X光检查中的架构变形

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Mammography is a widely used screening tool for the early detection of breast cancer. One of the commonly missed signs of breast cancer is architectural distortion. The purpose of this study is to explore the application of fractal analysis and texture measures for the detection of architectural distortion in screening mammograms taken prior to the detection of breast cancer. A method based on Gabor filters and phase portrait analysis was used to detect initial candidates of sites of architectural distortion. A total of 386 regions of interest (ROIs) were automatically obtained from 14 "prior mammograms", including 21 ROIs related to architectural distortion. The fractal dimension of the ROIs was calculated using the circular average power spectrum technique. The average fractal dimension of the normal (false-positive) ROIs was higher than that of the ROIs with architectural distortion. For the "prior mammograms", the best receiver operating characteristics (ROC) performance achieved was 0.74 with the fractal dimension and 0.70 with fourteen texture features, in terms of the area under the ROC curve.
机译:乳房X线照相是一种广泛使用的筛选工具,用于早期检测乳腺癌。乳腺癌的常见迹象之一是建筑扭曲。本研究的目的是探讨分形分析和纹理措施的应用,以检测乳腺癌前筛选乳腺照片的筛选乳腺照片。基于Gabor滤波器和相位纵向分析的方法用于检测建筑失真网站的初始候选。共有386个兴趣区域(ROI)自动从14个“先前的乳房X光线”中获得,其中包括21个与建筑扭曲有关的ROI。使用圆形平均功谱技术计算ROI的分形尺寸。正常(假阳性)ROI的平均分形尺寸高于ROI,具有架构扭曲的ROI。对于“先前的乳房X线图”,实现的最佳接收器操作特性(ROC)性能为0.74,分形尺寸和0.70,在ROC曲线下的区域方面具有十四个纹理特征。

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