ANALYSIS OF SPICULATION IN THE COMPUTERIZED CLASSIFICATION OF MAMMOGRAPHIC MASSES
ANALYSIS OF SPICULATION IN THE COMPUTERIZED CLASSIFICATION OF MAMMOGRAPHIC MASSES
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DOI：
10.1118/1.597626
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发表时间：
1995-10-01
期刊：
影响因子：
3.8
通讯作者：
SCHMIDT, RA
中科院分区：
文献类型：
--
作者：
HUO, ZM;GIGER, ML;SCHMIDT, RA
毛刺是乳房X光检查发现的肿块恶性的主要征兆。在这项研究中，我们开发了一种分析模式并量化存在的毛刺程度的技术。我们目前的方法包括(1)基于区域生长的自动病变提取和(2)基于径向边缘梯度分析的特征提取。通过对径向边缘梯度的分析，得到了两个毛刺度量。这些措施在四个不同的社区进行了评估，这些社区都是关于提取的乳房X光检查肿块的。在95个乳房X光检查肿块的数据库中，使用ROC分析来评估它们判断肿块恶变可能性的个体能力，以测试这两种毛刺测量方法的性能。分析了这些方法的性能对邻域选择的依赖关系。我们发现，为了这一分析的目的，只需要准确地提取肿块病变的大致轮廓，因为选择容纳边缘细针的邻域允许使用径向边缘梯度分析技术来评估边缘毛刺。当提取区域的周围用于特征提取时，这两个测量在它们的最高水平上执行，产生用于确定恶性的A(Z)值分别为0.83和0.85。这与单独使用放射科医生对毛刺的评分(A(Z)=0.85)时所获得的结果相似。四个社区的两个毛刺测量(FWHM)之一的最大值在乳腺摄影肿块病变分类中的A(Z)为0.88。
Spiculation is a primary sign of malignancy for masses detected by mammography. In this study, we developed a technique that analyzes patterns and quantifies the degree of spiculation present. Our current approach involves (1) automatic lesion extraction using region growing and (2) feature extraction using radial edge-gradient analysis. Two spiculation measures are obtained from an analysis of radial edge gradients. These measures are evaluated in four different neighborhoods about the extracted mammographic mass. The performance of each of the two measures of spiculation was tested on a database of 95 mammographic masses using ROC analysis that evaluates their individual ability to determine the Likelihood of malignancy of a mass. The dependence of the performance of these measures on the choice of neighborhood was analyzed. We have found that it is only necessary to accurately extract an approximate outline of a mass lesion for the purposes of this analysis since the choice of a neighborhood that accommodates the thin spicules at the margin allows for the assessment of margin spiculation with the radial edge-gradient analysis technique. The two measures performed at their highest level when the surrounding periphery of the extracted region is used for feature extraction, yielding A(z) values of 0.83 and 0.85, respectively, for the determination of malignancy. These are similar to that achieved when a radiologist's ratings of spiculation (A(z) = 0.85) are used alone. The maximum value of one of the two spiculation measures (FWHM) from the four neighborhoods yielded an A(z) of 0.88 in the classification of mammographic mass lesions.