分数阶Fourier变换(fractional Fourier transform, FrFT)是传统的Fourier变换在分数级次上的推广，它同时包含了信号时频域的信息.对乳腺肿瘤超声图像进行分数阶Fourier变换，提取分数阶Fourier变换域相位信息的统计纹理特征，并结合AdaBoost分类算法，实现乳腺肿瘤的良恶性分类.实验结果表明，基于分数阶Fourier变换提取的纹理特征能较好地应用于乳腺肿瘤的良恶性分类，说明该方法可用于乳腺肿瘤的计算机辅助诊断.

Fractional Fourier transform (FrFT) is a generalized form of the traditional Fourier transform, which includes information of both the time domain and the frequency domain. FrFT is used to extract phasebased features of breast tumor from ultrasound images. These features are used as input to the AdaBoost algorithm to distinguish benign tumors from malignant tumors. Experimental results indicate that the texture features extracted with the proposed FrFTbased algorithm can well classify breast tumor, and can be used in computeraided breast diagnosis.