基于升阶K分布统计特征的超声图像增强技术  

Ultrasound Image Enhancement Based on Statistical Characteristics of Ascending K Distribution

作　　者：蔡润秋 Cai Runqiu(Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing Jiangsu 210000,China)

机构地区：[1]南京中医药大学附属医院,江苏南京210000

出　　处：《医疗装备》2022年第13期4-7,共4页Medical Equipment

摘　　要：超声回波信号图像不仅可以提供组织反射波的强度信息,还蕴含着图像统计信息,工程师可以从来自不同组织结构的超声回波信号中提取相应的统计参数。该研究通过分析各种组织结构的统计分布来提取相应的统计参量,提出一种基于统计熵值权重图的图像增强方法;通过基于升阶K分布对上述组织结构超声回波信号的统计分布进行建模,并实际采集超声图像对该模型进行验证,证实该图像增强方法可以提高对特定组织结构的识别能力;通过对该方法的进一步讨论发现,统计熵值权重图可为识别正常组织结构的病理变化提供有效的参考。Ultrasonic echo signal image can not only provide the intensity information of tissue reflected wave,but also contain statistical information of the image,so engineers can extract corresponding statistical parameters from ultrasonic echo signals from different tissue structures.This study extracted the corresponding statistical parameters by analyzing the statistical distribution of various tissue structures,and proposed an image enhancement method based on statistical entropy weight graph.The statistical distribution of ultrasonic echo signals of the above mentioned tissue structures was modeled based on ascending K distribution,and the ultrasonic images were collected actually to verify the model.It was confirmed that the image enhancement method can improve the recognition ability of specific tissue structures.The further discussion of this method showed that the statistical entropy weight graph can provide an effective reference for identifying the pathological changes of normal tissue structures.

关 键 词：超声图像 统计分布 拓扑 

分 类 号：R318[医药卫生—生物医学工程]