摘要
远聚焦像素(far-focused pixel-based,FPB)成像算法是对成像区域外进行聚焦,对成像区域内的每个像素点进行成像,因此在整个成像区域内均能保持较高的成像分辨率。然而,FPB一般采用直接叠加的方式进行成像,成像质量有待进一步提高。广义相干系数(generalized coherence factor,GCF)加权算法可以有效地改善成像的对比度和分辨率。本研究根据FPB在不同深度时像素点复合次数的不同,提出了基于深度可调节的广义相干系数(adjustable generalized coherence factor,aGCF),该系数可根据成像深度自主调节GCF的计算参数,从而提高该系数的远场性能。再将aGCF和归一化自相关系数(normalized autocorrelation factor,NAF)融合后,进行加权成像。仿真和实验结果表明,新加权算法相比于FPB算法可明显改善成像的分辨率和对比度,相对于传统的GCF算法可在成像区域的近场内提高横向分辨率,远场内改善对比度和背景成像质量。
Far-focused pixel-based(FPB)imaging algorithm can maintain a high imaging resolution throughout the imaging area,by focusing on outside the imaging region and imaging each pixel in the imaging area.However,FPB generally uses the conventional delay-and-sum to reconstruct images,so the imaging quality needs to be further improved.The generalized coherence factor(GCF)weighting algorithm can effectively improve the image contrast and resolution.We proposed an adjustable generalized coherence factor(aGCF)according to the different composite times of FPB pixels at different depths,which could adaptively adjust the calculation parameters of GCF according to the imaging depth,thereby improving imaging performance in the far-field region.After fusing of AGCF and normalized autocorrelation factor(NAF),weighted imaging was performed.Simulation and experimental results show that compared to FPB,the new weighting algorithm improves image resolution and contrast significantly.Compared with the traditional GCF algorithm,it improves the lateral resolution in the near field,and improves the contrast and background imaging quality in the far field.
作者
徐祥
汪亚中
郑驰超
彭虎
XU Xiang;WANG Yazhong;ZHENG Chichao;PENG Hu(Department of Biomedical Engineering,Hefei University of Technology,Hefei 230009,China)
出处
《生物医学工程研究》
2020年第4期319-329,共11页
Journal Of Biomedical Engineering Research
基金
国家自然科学基金资助项目(61201060,61172037)。
关键词
超声成像
远聚焦像素成像
可调节的广义相干系数
归一化自相关系数
对比度
背景成像质量
Ultrasound imaging
Far-focused pixel-based imaging
Adjustable generalized coherence factor
Normalized autocorrelation factor
Contrast
Background imaging quality
作者简介
通信作者:郑驰超,Email:cczheng@hfut.edu.cn。
