Objective: As an aided diagnostic method for medical ultrasound systems, radio-frequency characteristic signal processing enables doctors to increase the recognition rate for certain diseases, the aim of ultrasound RF signal processing is to acquire the corresponding parameters with clinical aids. Methods: The raw radio-frequency data, collected from the backstage databank of VINNO 70 ultrasound scanner, was compiled into manageable matrix format. Then the breast lump region and normal tissue region labelled in the data matrix, was processed by standard variance and entropy algorithms compiled using Matlab. Results:The results indicate the entropy and standard deviation of normal region is higher than lump region about 40%. Conclusion: The analysis of results conclude the effectivity of the standard variance and entropy algorithms to recognize the breast lump region and the normal tissue region.%目的：对超声射频信号进行数据编译与信号处理研究，得到具有临床诊断意义的相关特征参数，用以辅助乳腺肿块的临床诊断。方法：将VINNO 70超声诊断平台的后台数据库提供的超声射频信号数据，在Matlab软件系统中编写标准差及熵值算法，处理数值矩阵中肿块区域与正常组织区域数值，以得到乳腺肿块区域参数。结果：通过标准差及熵值算法的处理显示，正常区域的熵值及标准差数值比肿块区域均高出40%。结论：超声射频信号特征算法中的标准差及熵值算法处理，能够有效区别乳腺肿块区域与正常组织区域。
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