一种基于B超图像处理的生物组织变性监测方法

本文提出基于B超图像灰度和小波变换系数并结合BP神经网络监测HIFU治疗中生物组织变性的方法。通过对高强度聚焦超声打击新鲜离体猪肉组织前后获得的B超图像作数字减影,并提取图像特征,利用神经网络进行分类处理。在此基础上,对大量实验数据处理后的统计特性和误差进行分析,得出较好的辨识效果。结果表明:结合图像平均灰度和小波变换系数特征并输入BP神经网络,能够更好地监测HIFU治疗中生物组织是否变性。

A Method to Check Biological Tissue Denaturation Based on Mode B Ultrasonic Image Processing

A method using BP neural network was presented to check biological tissue denaturation based on grey value and wavelet transform coefficient of Mode B Ultrasonic Image in HIFU treatment.The digital subtraction was executed for mode B ultrasonic images obtained from fresh vitro pork before and after HIFU radiation,and then its image features were extracted and classified by neural network.Through analyzing the statistical properties and errors of plentiful experimental data,the distinguishing effects could be obtained with finished.The results show that combining the average grey with the wavelet transform coefficient to construct BP neural network,the denaturation of biological tissue can be monitored better during HIFU therapy.