Lensless microfluidic imaging based cell detection and counting system

HUANG Xi-wei; CHENG Tao; DING Cheng-xiang; WANG Xiang; GAO Hai-jun; SU Jiang-tao

doi:10.13873/j.1000-9787(2017)05-0094-05

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Lensless microfluidic imaging based cell detection and counting system

更新时间：2025-09-11

- Lensless microfluidic imaging based cell detection and counting system
- Vol. 36, Issue 5, Pages: 94-98(2017)
- 作者机构：
  
  杭州电子科技大学射频电路与系统教育部重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2017)05-0094-05
  CLC： TP212;TP391.41
- Published：2017
- 稿件说明：
移动端阅览
[1]黄汐威,程涛,丁诚翔,王翔,高海军,苏江涛.无透镜微流控成像流动细胞检测与计数系统[J].传感器与微系统,2017,36(05):94-98.

HUANG Xi-wei, CHENG Tao, DING Cheng-xiang, et al. Lensless microfluidic imaging based cell detection and counting system[J]. 2017, 36(5): 94-98.
[1]黄汐威,程涛,丁诚翔,王翔,高海军,苏江涛.无透镜微流控成像流动细胞检测与计数系统[J].传感器与微系统,2017,36(05):94-98. DOI： 10.13873/j.1000-9787(2017)05-0094-05.

HUANG Xi-wei, CHENG Tao, DING Cheng-xiang, et al. Lensless microfluidic imaging based cell detection and counting system[J]. 2017, 36(5): 94-98. DOI： 10.13873/j.1000-9787(2017)05-0094-05.

摘要

在未来面向个人化的生物医疗诊断中

实时的细胞检测与计数具有重要需求。现有的细胞检测和计数系统例如流式细胞仪和血细胞计数器不适用于小型化流动细胞实时检测和计数。通过将CMOS图像传感器芯片和微流控芯片结合

提出了一种用于流动细胞检测和计数的无透镜微流控成像系统

与用于计数静态细胞的其它无透镜微流控成像系统不同

该系统可以通过基于时域差分的运动检测算法检测和计数微流体通道中连续流动的细胞样本。测试结果表明:该系统可以对微流控通道中流动的人体骨髓基质细胞实现自动检测和计数

并具有-6.53%的低统计错误率。该系统提供了面向未来即时应用的细胞检测和计数解决方案。

Abstract

The existing cell detection and counting systems such as flow cytometer and haemocytometer are not designed towards real-time for cells in flowing microfluid. Based on the integration of a CMOS image sensor and a microfluidic chip

a lensless microfluidic imaging system for detection and counting of flowing cells is presented.Different from the other lensless microfluidic imaging systems designed for counting static cells

the developed system can detect and count continuously flowing cells in microfluidic channel by temporal-differencing based motion detection algorithms. Measured experiment results show that human bone marrow stromal cells flowing in the microfluidic channel can be automatically detected and counted with low statistical error rate of-6. 53 %. The developed system thereby provides cell detection and counting solutions for point-of-care applications.

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references

临床检验装备大全[M]. 科学出版社 , 丛玉隆, 2015

Lensless Imaging and Sensing [J] . Aydogan Ozcan,Euan McLeod. Annual Review of Biomedical Engineering . 2016

Advances in addressing technical challenges of point-of-care diagnostics in resource-limited settings [J] . Wang,Lifson,Inci,Liang,Sheng,Demirci. Expert Review of Molecular Diagnostics . 2016 (4)

Point-of-care testing （POCT） diagnostic systems using microfluidic lab-on-a-chip technologies [J] . Wooseok Jung,Jungyoup Han,Jin-Woo Choi,Chong H. Ahn. Microelectronic Engineering . 2015

Enabling the Development and Deployment of Next Generation Point-of-Care Diagnostics [J] . Ratmir Derda,Jesse Gitaka,Catherine M. Klapperich,Charles R. Mace,Ashok A. Kumar,Marya Lieberman,Jacqueline C. Linnes,Joerg Jores,Johnson Nasimolo,Joseph Ndung’u,Evans Taracha,Abigail Weaver,Douglas B. Weibel,Thomas M. Kariuki,Paul Yager. PLOS Neglected Tropical Diseases . 2015 (5)

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