基于Gabor变换和灰度梯度共生矩阵的超声无损测温研究

发布时间：2018-01-30 23:19

  本文关键词： 高强度聚焦超声 无损测温 Gabor变换 灰度共生梯度矩阵　出处：《传感技术学报》2017年11期 　论文类型：期刊论文

【摘要】：提出了一种基于Gabor变换和灰度梯度共生矩阵(CMGG)的超声无损测温方法。通过高强度聚焦超声(HIFU)对新鲜离体猪肉组织进行辐照,实时获取辐照前后的超声图像,对其做数字减影和Gabor滤波,提取归一化后灰度梯度共生矩阵的二阶参数梯度平均、混合熵和逆差矩作为温度的表征参数。实验结果表明:Gabor滤波后的灰度-梯度共生矩阵的二阶参数梯度平均、混合熵和逆差矩与温度的相关系数分别达到0.980 4、0.985 4和-0.964 4,优于传统的灰度均值法和实值Gabor系数法。Gabor滤波后的灰度-梯度共生矩阵的二阶参数混合熵在37℃~55℃能较好地反映温度变化信息,梯度平均则在55℃~85℃有更好的测温效果。
[Abstract]:A new ultrasonic nondestructive temperature measurement method based on Gabor transform and gray-scale gradient co-occurrence matrix was proposed. High intensity focused ultrasound (HIFU) was used to irradiate fresh pork tissues in vitro. The ultrasonic images before and after irradiation were obtained in real time. Digital subtraction and Gabor filtering were performed to extract the second-order parameter gradient average of normalized gray gradient co-occurrence matrix. The experimental results show that the gray-gray-gradient co-occurrence matrix of the gray-gradient co-occurrence matrix obtained by the weighted Gabor filter has a second-order parametric gradient average. The correlation coefficients between the mixing entropy and the unfavorable moment and the temperature are 0.9804 ~ 0.985 4 and -0.964 4, respectively. The mixed entropy of second-order parameters of gray-gradient co-occurrence matrix is better than the traditional gray mean method and real Gabor coefficient method. It can reflect the temperature change information at 37 鈩，

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