Automatic elasticity measurement of single cells using a microfluidic system with real-time image processing

被引:0
|
作者
Cai, Yike [1 ]
Chen, Siyuan [1 ]
Xu, Dong [1 ]
Guo, Tianruo [2 ]
Jin, Jing [1 ]
Chen, Huaying [1 ]
机构
[1] Harbin Inst Technol, Sch Mech Engn & Automat, Shenzhen, Peoples R China
[2] UNSW, Grad Sch Biomed Engn, Sydney, NSW, Australia
基金
中国国家自然科学基金;
关键词
DEFORMABILITY;
D O I
10.1109/EMBC40787.2023.10340799
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The mechanical properties of cells are closely related to their physiological states and functions. Due to the limitations of conventional cell elasticity measurement technologies such as low throughput, cell-invasiveness, and high cost, microfluidic systems are emerging as powerful tools for high-throughput cell mechanical property studies. This paper introduces a microfluidic system to automatically measure the elastic modulus of single cells in real time. The system integrated a microfluidic chip with a microchannel for cell constriction, a pressure pump, a precision differential pressure sensor, and a program for online analysis of cell deformation. The program used a fast U-net to segment cell images and measure protrusion length during cell deformation. Subsequently, the cell elasticity was determined in real-time based on the deformation and required pressure using the power law rheological model. Finally, Young's modulus of BMSCs, Huh-7 cells, EMSCs, and K562 cells was measured as 25.13 +/- 15.19 Pa, 69.74 +/- 92.01 Pa, 54.50 +/- 59.31 Pa and 58.43 +/- 27.27 Pa, respectively. The microfluidic system has significant application potential in the automated evaluation of cell mechanical properties.
引用
收藏
页数:4
相关论文
共 50 条
  • [41] Implementation of real-time digital endoscopic image processing system
    Song, CG
    Lee, YM
    Lee, SM
    Kim, WK
    Lee, JH
    Lee, MH
    APPLICATIONS OF DIGITAL IMAGE PROCESSING XX, 1997, 3164 : 650 - 658
  • [42] Real-time motional image processing in intelligent vehicle system
    Yang, Ying
    Zhao, Guangyao
    DCABES 2006 Proceedings, Vols 1 and 2, 2006, : 405 - 407
  • [43] Programming tool for real-time image processing on a distributed system
    Arita, D
    Hamada, Y
    Taniguchi, R
    PARALLEL AND DISTRIBUTED METHODS FOR IMAGE PROCESSING III, 1999, 3817 : 28 - 39
  • [44] The real-time processing system of infrared and LLL image fusion
    Qian Yunsheng
    Zhang Junju
    Tian Shi
    Chao Qian
    Zhou Zixiang
    Chang Benkang
    INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2007: IMAGE PROCESSING, 2008, 6623
  • [45] Real-time image processing system for IRFPA based on FPGA
    School of Technical Physics, Xidian University, Xi'an 710071, China
    Hongwai yu Jiguang Gongcheng Infrared Laser Eng., 2006, 6 (655-658):
  • [46] A customisable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel
    Coffey, S
    Connell, J
    Opto-Ireland 2005: Imaging and Vision, 2005, 5823 : 245 - 257
  • [47] Real-time measurement of cardiomyocyte contraction and calcium transients using fast image processing algorithms
    Cmiel, V.
    Odstrcilik, J.
    Ronzhina, M.
    Provaznik, I.
    WORLD CONGRESS ON MEDICAL PHYSICS AND BIOMEDICAL ENGINEERING, 2015, VOLS 1 AND 2, 2015, 51 : 256 - 259
  • [48] Automatic real-time focus control system for laser processing using dynamic focusing optical system
    Cao, Binh Xuan
    Phuong Hoang Le
    Ahn, Sanghoon
    Kang, Heeshin
    Kim, Jengo
    Noh, Jiwhan
    OPTICS EXPRESS, 2017, 25 (23): : 28427 - 28441
  • [49] Spectral image processing in real-time
    Carlsohn, Matthias F.
    JOURNAL OF REAL-TIME IMAGE PROCESSING, 2006, 1 (01) : 25 - 32
  • [50] Spectral image processing in real-time
    Matthias F. Carlsohn
    Journal of Real-Time Image Processing, 2006, 1 : 25 - 32