广义序列动态成像

Zhi-Pei Liang
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引用次数: 4

摘要

许多成像应用需要采集时间序列的图像。在传统的基于傅里叶变换的成像方法中,每个图像都是独立获取的。因此,可能的时间分辨率受到每个数据集收集的数据点数量的限制,或者通常是为了时间分辨率而牺牲空间分辨率。为了克服这个问题,提出了几种“数据共享”方法,这些方法获取一个或多个高分辨率参考图像和一系列简化的动态数据集。本文讨论了一种基于广义序列的动态成像方法,该方法是数据共享原则的最佳实现。应用实例说明了该方法在高分辨率动态成像中的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized series dynamic imaging
Many imaging applications require the acquisition of a time series of images. In conventional Fourier transform-based imaging methods, each of these images is acquired independently. As a result, the temporal resolution possible is limited by the number of data points collected for each data set, or one often was to sacrifice spatial resolution for temporal resolution. To overcome this problem, several "data-sharing" methods have been proposed which acquire one or more high-resolution reference images and a sequence of reduced dynamic data sets. This paper is devoted to the discussion of a generalized series-based dynamic imaging method, which is an optimal implementation of the data-sharing principle. Several application examples are also presented to illustrate its effectiveness for high-resolution dynamic imaging.
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