Pectoral Muscle Boundary Detection in Mammograms Using Homogeneous Contours

R. Lakshmanan, Shiji T. P, V. Thomas, S. M. Jacob, Thara P
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引用次数: 5

Abstract

Breast occupies over Pectoral muscle (PM) which is a predominant portion in Medio-Lateral Oblique (MLO) view of mammogram. The similarity in density among PM area and the breast region may generate false positive results which can adversely affect early breast cancer detection. Noise, wedges, opaque markers etc along with labels are unnecessary in mammographic images. The suspicious segments of PM boundary are obtained by extracting contours of homogeneous regions. The geometrical properties of contour segments are analyzed for extracting PM boundary component. An intensity similarity approach extends the detected major PM boundary segment to the two boundaries of mammogram. Experimental analyses were carried out on mammograms obtained from Mammographic Image Analysis database. The proposed methods yields low values for average false positive, average false negative and Hausdorff distance. From the performance analysis of the proposed algorithm, 97% of images have an average error less than 4 mm. Low values of performance measures for the proposed method shows that the extracted PM boundary is close to radiologist drawn PM border.
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均匀轮廓在乳房x线照片中的胸肌边界检测
乳房占据胸肌(PM),这是乳房x光片中-外侧斜位(MLO)视图的主要部分。PM区与乳腺区域密度相似,可能产生假阳性结果,对早期乳腺癌的检测产生不利影响。在乳房x线摄影图像中,噪音、楔形、不透明标记等都是不必要的。通过提取均匀区域的轮廓,得到PM边界的可疑段。分析了等高线段的几何性质,提取了PM边界分量。强度相似方法将检测到的主要PM边界段扩展到乳房x光片的两个边界。实验分析从乳腺图像分析数据库中获得的乳房x线照片。所提方法的平均假阳性、平均假阴性和豪斯多夫距离的值都很低。从算法的性能分析来看,97%的图像平均误差小于4 mm。该方法的低性能度量值表明,提取的PM边界接近放射科医生绘制的PM边界。
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