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光学流算法在激光散斑成像中的应用。

Application of optical flow algorithms to laser speckle imaging.

机构信息

Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America.

Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, United States of America.

出版信息

Microvasc Res. 2019 Mar;122:52-59. doi: 10.1016/j.mvr.2018.11.001. Epub 2018 Nov 8.

Abstract

Since of its introduction in 1980s, laser speckle imaging has become a powerful tool in flow imaging. Its high performance and low cost made it one of the preferable imaging methods. Initially, speckle contrast measurements were the main algorithm for analyzing laser speckle images in biological flows. Speckle contrast measurements, also referred as Laser Speckle Contrast Imaging (LSCI), use statistical properties of speckle patterns to create mapped image of the blood vessels. In this communication, a new method named Laser Speckle Optical Flow Imaging (LSOFI) is introduced. This method uses the optical flow algorithms to calculate the apparent motion of laser speckle patterns. The differences in the apparent motion of speckle patterns are used to identify the blood vessels from surrounding tissue. LSOFI has better spatial and temporal resolution compared to LSCI. This higher spatial resolution enables LSOFI to be used for autonomous blood vessels detection. Furthermore, Graphics Processing Unit (GPU) based LSOFI can be used for quasi real time imaging.

摘要

自 20 世纪 80 年代问世以来,激光散斑成像已成为血流成像的有力工具。其高性能和低成本使其成为首选成像方法之一。最初,散斑对比度测量是分析生物流中激光散斑图像的主要算法。散斑对比度测量,也称为激光散斑对比成像(LSCI),利用散斑图案的统计特性来创建血管的映射图像。在本通讯中,引入了一种称为激光散斑光流成像(LSOFI)的新方法。该方法使用光流算法来计算激光散斑图案的表观运动。散斑图案表观运动的差异用于从周围组织中识别血管。与 LSCI 相比,LSOFI 具有更好的空间和时间分辨率。这种更高的空间分辨率使 LSOFI 能够用于自主血管检测。此外,基于图形处理单元(GPU)的 LSOFI 可用于准实时成像。

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