微球测速聚类分析的流式液路稳定性评估

张文昌; 祝连庆; 娄小平; 刘超; 孟晓辰

doi:10.3788/OPE.20162401.0030

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微球测速聚类分析的流式液路稳定性评估

现代应用光学 | 更新时间：2020-08-13

- 微球测速聚类分析的流式液路稳定性评估
- Stability evaluation of flow cytometer liquid path based on cluster analysis of particle velocity
- 光学精密工程 2016年24卷第1期页码：30-38
- 作者机构：
  
  1. 合肥工业大学仪器科学与光电工程学院,安徽合肥,230009
  2. 北京信息科技大学光电测试技术北京市重点实验室北京,100101
- 作者简介：
- 基金信息：
  
  教育部长江学者和创新团队发展计划资助项目(No.IRT1212)();北京市市属高等学校创新团队建设提升计划资助项目(No.IDHT20130518)();北京市教委科
- DOI：10.3788/OPE.20162401.0030
  中图分类号： TH773
- 收稿日期：2015-06-19，
  
  修回日期：2015-08-15，
  
  纸质出版日期：2016-01-25
- 稿件说明：
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张文昌, 祝连庆, 娄小平等. 微球测速聚类分析的流式液路稳定性评估[J]. 光学精密工程, 2016,24(1): 30-38

ZHANG Wen-chang, ZHU Lian-qing, LOU Xiao-ping etc. Stability evaluation of flow cytometer liquid path based on cluster analysis of particle velocity[J]. Editorial Office of Optics and Precision Engineering, 2016,24(1): 30-38
张文昌, 祝连庆, 娄小平等. 微球测速聚类分析的流式液路稳定性评估[J]. 光学精密工程, 2016,24(1): 30-38 DOI： 10.3788/OPE.20162401.0030.

ZHANG Wen-chang, ZHU Lian-qing, LOU Xiao-ping etc. Stability evaluation of flow cytometer liquid path based on cluster analysis of particle velocity[J]. Editorial Office of Optics and Precision Engineering, 2016,24(1): 30-38 DOI： 10.3788/OPE.20162401.0030.

摘要

提出了一种基于90° Mie散射的高速图像采集微球测速方法

用于准确评估流式细胞仪流动室内的层流状态及单细胞流的稳定性。利用流动室内微球速度的稳定性对流动室内单细胞流的稳定性进行了评估。首先

利用高速显微成像系统采集90° Mie散射光的图像

选取90°侧向散射光以避免激发光源直射光的干扰

同时去除背景光源并提高图像对比度;然后

利用基于梯形白化权函数的灰色聚类分析方法对微球拖尾图像进行分类

实现对不足、正常、衍射和重叠4种情况的准确分类;最后

利用中点法确定正常图像上升沿及下降沿的边界

提高拖尾长度计算的准确性。搭建了高速微球测速实验系统

对本文方法进行验证。结果表明

该方法能够获得清晰的微球拖尾图像并对微球拖尾图像进行准确分类。对本文实验系统测得的微球拖尾长度平均值为116.9个像素点

标准差为1.7。

Abstract

A high-speed particle image velocimetry based on 90° Mie scattering was proposed to evaluate the status of laminar flow and single-cell flow stability in the flow cell of a flow cytometer. The velocity stability of the particles in the flow cell was used to evaluate the single-cell flow stability of the flow cytometer. Firstly

90° Mie scattering images of the particle were acquired with a high-speed image sampling system. The 90° Mie scattering selected could avoid the interference of the excitation light source and could remove the background source and improve the image contrast. Then

the grey cluster analysis algorithm based on trapezoid whitenization weight functions was used to classify for all different types of images with shortages

normal

diffraction and overlap. Finally

a center-point method was taken to determine the boundaries of the trailing image to improve the computational accuracy of the length of particle trailing. A experimental system was carried out to verify the feasibility of the comprehensive method. The results show that the method obtains distinct trailing images and they have been classified accurately. Moreover

for the system of this article

the average length of trailing image covers 116.9 pixels

and the standard deviation is 1.7.

关键词

Keywords

references

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