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目的:探讨良恶性肿瘤采用超声诊断量化的方法,从而为良恶性肿瘤的识别提供依据。方法:提取经手术确诊的20例良恶性乳腺肿瘤患者(良性与恶性各10例)的原始超声图像灰度特征资料,采用算法编程与Matoab7.0图像处理函数对良恶性患者图像的4个灰度特征参数进行计算,并对比参数在良性、恶性肿瘤间的差异。结果:良性肿瘤患者超声图像的灰度均值M、灰度标准差V与扭曲度S分别为60.5±11.8、27.6±4.7、0.2±0.1,恶性肿瘤患者超声图像的灰度均值M、灰度标准差V与扭曲度S分别为82.5±6.7、32.0±3.4、0.9±0.2,组间比较差异显著(P<0.05)。结论:超声图像定量分析对良恶性肿瘤超声图像的特征可起到量化作用,且M、V、S参数可为良恶性肿瘤的识别提供依据。
Objective: To investigate the method of ultrasonic diagnosis and quantification of benign and malignant tumors, and to provide basis for the identification of benign and malignant tumors. Methods: The original ultrasound image gray scale features of 20 cases of benign and malignant breast tumors (10 cases of benign and malignant tumors) were extracted from the surgically-diagnosed benign and malignant breast tumors. The algorithms of programming and Matoab7.0 image processing function were used to detect the four gray Degree characteristic parameters were calculated, and compared parameters in benign and malignant tumors. Results: The gray mean value M, gray standard deviation V and distortion S of benign tumor patients were 60.5 ± 11.8,27.6 ± 4.7 and 0.2 ± 0.1, respectively. The gray mean value M and gray standard of ultrasonic images of patients with malignant tumors The difference V and twist S were 82.5 ± 6.7, 32.0 ± 3.4 and 0.9 ± 0.2, respectively, with significant difference between the two groups (P <0.05). Conclusion: Quantitative analysis of ultrasound images can quantify ultrasonographic features of benign and malignant tumors, and M, V, S parameters can provide a basis for the identification of benign and malignant tumors.