Biomedical Engineering Program/COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-972, Brazil.
Comput Biol Med. 2010 Nov-Dec;40(11-12):912-8. doi: 10.1016/j.compbiomed.2010.10.003. Epub 2010 Oct 25.
Ultrasound breast images have been used to improve diagnostics and decrease the number of unneeded biopsies. Malignant breast tumors tend to present irregular and blurred contours while benign ones are usually round, smooth and well-defined. Accordingly, investigating the tumor contour may help in establishing diagnosis. Herein, Mutual Information and Linear Discriminant Analysis were implemented to rank morphometric features in discriminating breast tumors in ultrasound images. Seven features were extracted from Convex Polygon and the Normalized Radial Length techniques. By applying a Mutual Information based approach, it was possible to identity features with possibly non-linear contributions to the outcome.
超声乳腺图像已被用于提高诊断水平并减少不必要的活检数量。恶性乳腺肿瘤往往呈现不规则和模糊的轮廓，而良性肿瘤通常是圆形、光滑且界限分明的。因此，研究肿瘤轮廓有助于确定诊断。在此，使用互信息和线性判别分析对超声图像中的乳腺肿瘤的形态特征进行了排名。从凸多边形和归一化径向长度技术中提取了七个特征。通过应用基于互信息的方法，可以识别出可能对结果有非线性贡献的特征。
