反褶积
衍射
点扩散函数
声学
工件(错误)
微气泡
图像分辨率
计算机科学
信号(编程语言)
对比度(视觉)
极限(数学)
人口
分辨率(逻辑)
超声波
光学
物理
计算机视觉
人工智能
数学
医学
数学分析
程序设计语言
环境卫生
作者
Kang Kim,Qiyang Chen,Jaesok Yu
摘要
Contrast enhanced ultrasound (CEU) imaging technologies using microbubbles (MBs) provide superior contrast of vasculatures, effectively suppressing the surrounding tissue signals, but the spatial resolution remains to the acoustic diffraction limit. By localizing the center of each MBs unprecedented high spatial resolution beyond the acoustic diffraction limit can be achieved. However, some methods of localizing each center of the signals from individual MBs that only applies symmetrically distributed signal amplitude require a large number of imaging frames, especially when MBs are densely clumped, therefore result in a long scan time that is not ideal for in vivo scan under physiologic conditions. In this paper, we present an innovative approach using deconvolution technique that will allow for identifying signals from individual MBs from dense population in any forms even grouped together within the full-width-at-half-maximum (FWHM) of the point spread function (PSF) of the US probe. In this way, no collected frame sets require to be excluded for image reconstruction, therefore scan time can be reduced significantly. In vivo application of this new approach in identifying vasa vasorum in rabbit atherosclerotic plaque model will be presented. Some technical limitations including background noise as well as motion artifact will be discussed.
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