Application of optical flow algorithms to laser speckle imaging
Application of optical flow algorithms to laser speckle imaging
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DOI：
10.1016/j.mvr.2018.11.001
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发表时间：
2019-03-01
影响因子：
3.1
通讯作者：
Princevac, Marko
中科院分区：
文献类型：
--
作者：
Aminfar, AmirHessam;Davoodzadeh, Nami;Princevac, Marko
激光散斑成像自20世纪80年代问世以来，已成为流场成像的有力工具。它的高性能和低成本使其成为较好的成像方法之一。最初，散斑对比度测量是生物流中激光散斑图像分析的主要算法。散斑对比测量，也被称为激光散斑对比成像（LSCI），利用散斑模式的统计特性来创建血管的映射图像。本文介绍了一种新的激光散斑光流成像方法。该方法利用光流算法计算激光散斑图的视运动。斑点模式的表观运动差异被用来从周围组织中识别血管。与LSCI相比，LSOFI具有更好的时空分辨率。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。
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.