Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia.
Comput Med Imaging Graph. 2010 Jun;34(4):269-76. doi: 10.1016/j.compmedimag.2009.11.002. Epub 2009 Dec 9.
This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms.
本文提出了一种基于曲波变换的乳腺 X 线图像计算机辅助诊断方法。首先对乳腺 X 线图像进行曲波分解，提取最大系数作为特征向量，然后采用欧氏距离建立分类器。实验结果表明，该方法的分类准确率达到 98.59%，表明曲波变换是一种很有前途的乳腺 X 线图像分析和分类工具。
