基于频谱图像灰度共生矩阵的无损测温方法

本文提出了一种基于哈达玛变换的频谱图像灰度共生矩阵(Hadamard-GLCM)的高强度聚焦超声治疗无损测温方法。利用高强度聚焦超声辐照新鲜离体猪肉组织,获取辐照前后的B超图像的减影图像,采用Hadamard变换对其进行处理,获取频谱图像,将频谱图像的灰度共生矩阵惯性矩作为反应温度变化的信息参数。实验表明:不仅单组数据的Hadamard-GLCM惯性矩(HGMI)和温度能很好的线性拟合,而且多组数据的Hadamard-GLCM惯性矩与温度也成近似的线性关系,而且斜率非常接近,拟合度更接近1,误差小,对温度的分辨能力高,容错能力强,与传统的测温方法相比有着明显的优势,能为HIFU治疗过程中的无损测温提供有效的实时依据。

Method of Noninvasive Temperature Estimation Based on Gray Level Co-Occurrence Matrix of Spectral Image

A method of noninvasive temperature estimation for high intensity focused ultrasound (HIFU)therapy based on gray level co-occurrence matrix of Hadamard spectral image (Hadamard-GLCM)is presented.The fresh pork was ir-radiated in vitro by HIFU,the subtraction image is obtained from real-time B-mode ultrasound images before and after ir-radiation.Hadamard-GLCM’s moment of inertia(HGMI)as the parameters about the temperature information was sepa-rated from spectral image which was obtained from the subtraction image by use of Hadamard’s transform.The results show that not only the Hadamard-GLCM’s moment of inertia in single group data can be a very well linear fitting with the temperature,but the multiple sets of pictures data can also do.The scope of multiple sets of pictures data are very close proximity and the fitting is very close to 1,this method has the smaller error,higher temperature resolution and stronger fault tolerance.Compared with the traditional temperature estimation method,this method has obviously advantages that it is able to provide the real-time basis for the effective HIFU treatment of noninvasive temperature estimation.