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Tracking Red Blood Cells Flowing through a Microchannel with a Hyperbolic Contraction: An Automatic Method

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Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 19))

Abstract

The present chapter aims to assess the motion and deformation index of red blood cells (RBCs) flowing through a microchannel with a hyperbolic contraction using an image analysis based method. For this purpose, a microchannel containing a hyperbolic contraction was fabricated in polydimethylsiloxane by using a soft-lithography technique and the images were captured by a standard high-speed microscopy system. An automatic image processing and analyzing method has been developed in a MATLAB environment, not only to track both healthy and exposed RBCs motion but also to measure the deformation index along the microchannel. The keyhole model has proved to be a promising technique to track automatically healthy and exposed RBCs flowing in this kind of microchannels.

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References

  1. Abkarian M, Faivre M, Horton R, Smistrup K, Best-Popescu CA, Stone HA (2008) Cellularscale hydrodynamics. Biomed Mater 3(3):034011

    Article  Google Scholar 

  2. Brox T, Bruhn A, Papenberg N, Weickert J (2004) High accuracy optical flow estimation based on a theory for warping. In: PajdlaT, Matas J (eds) European conference on computer vision, vol. 3024. Springer, LNCS, pp 25–36

    Google Scholar 

  3. Bruhn A, Weickert J, Schnörr C (2005) Luca/Kanade meets Horn/Schunck: combining local and global optic flow methods. Int J Comput Vision 61(3):1–21

    Article  Google Scholar 

  4. Carter BC, Shubeita GT, Gross SP (2005) Tracking single particles: a user-friendly quantitative evaluation. Phys Biol 2:60–72

    Article  Google Scholar 

  5. Crocker JC, Grier DG (1996) Methods of digital video microscopy for colloidal studies. J Colloid Interface Sci 179(1):298–310

    Article  Google Scholar 

  6. Faustino V, Pinho D, Yaginuma T, Calhelha R, Ferreira I, Lima R (2014) Ex-tensional flow-based microfluidic device: deformability assessment of red blood cells in contact with tumor cells. BioChip J 8:42–47

    Article  Google Scholar 

  7. Fujiwara H, Ishikawa T et al (2009) Red blood cell motions in high-hematocrit blood flowing through a stenosed microchannel. J Biomech 42:838–843

    Article  Google Scholar 

  8. Garcia V, Dias R, Lima R (2012) In vitro blood flow behaviour in microchannels with simple and complex geometries. In: Naik GR (ed) Applied biological engineering–principles and practice. InTech, Rijeka, pp 393–416

    Google Scholar 

  9. Horn BKP, Schunck BG (1981) Determining optical flow. Artif Intell 17(1–3):185–203

    Article  Google Scholar 

  10. Leble V, Lima R, Dias R, Fernandes C, Ishikawa T, Imai Y, Yamaguchi T (2011) Asymmetry of red blood cell motions in a microchannel with a diverging and converging bifurcation. Biomicrofluidics 5:044120

    Article  Google Scholar 

  11. LimaR (2007) Analysis of the blood flow behavior through microchannels by a confocal micro-PIV/PTV system. PhD (Eng), Bioengineering and Robotics Department, Tohoku University, Sendai, Japan

    Google Scholar 

  12. Lima R, Ishikawa T et al (2009) Measurement of individual red blood cell motions under high hematocrit conditions using a confocal micro-PTV system. Ann Biomed Eng 37:1546–1559

    Article  Google Scholar 

  13. Lima R, Ishikawa T, Imai Y, Takeda M, Wada S, Yamaguchi T (2008) Radial dispersion of red blood cells in blood flowing through glass capillaries: role of heamatocrit and geometry. J Biomech 44:2188–2196

    Article  Google Scholar 

  14. Lima R, Oliveira MSN, Ishikawa T, Kaji H, Tanaka S, Nishizawa, M, Yamaguchi T (2009) Axisymmetric PDMS microchannels for in vitro haemodynamics studies. Biofabrication 1(3):035005

    Article  Google Scholar 

  15. Lima R, Ishikawa T, Imai Y, Yamaguchi T (2012) Blood flow behavior in microchannels: advances and future trends. In: Dias R et al (eds) Single and two-phase flows on chemical and biomedical engineering. Bentham Science, Sharjah, pp 513–547

    Google Scholar 

  16. Lima R, Ishikawa T, Imai Y, Yamaguchi T (2013) Confocal micro-PIV/PTV measurements of the blood flow in micro-channels. In: Collins MW, König CS (eds) Nano and micro flow systems for bioanalysis, vol. 2. Springer, New York, pp 131–151

    Google Scholar 

  17. Lucas BD, Kanade T (1981) An iterative image registration technique with an application to stereo vision. Proceedings of Imaging Understanding Workshop, pp 121–130

    Google Scholar 

  18. Meijering E, Dzyubachyk O, Smal I (2012) Methods for cell and particle tracking. In: Conn PM (ed) Imaging and spectroscopic analysis of living cells. Methods in enzymology, vol. 504. Elsevier, Amsterdam, pp 183–200

    Google Scholar 

  19. Pinho D, Yaginuma T, Lima R (2013) A microfluidic device for partial cell separation and deformability assessment. BioChip J 7:367–374

    Article  Google Scholar 

  20. Pinho D, Gayubo F, Pereira AI, Lima R (2013) A comparison between a manual and automatic method to characterize red blood cell trajectories. Int J Numer Meth Biomed Eng 29(9):977–987

    Article  MathSciNet  Google Scholar 

  21. Reyes-Aldasoro CC, Akerman S, Tozer G (2008) Measuring the velocity of fluorescently labelled red blood cells with a keyhole tracking algorithm. J Microsc 229(1):162–173

    Article  MathSciNet  Google Scholar 

  22. Rodrigues R, Faustino V, Pinto E, Pinho D, Lima R (2014) Red blood cells deformability index assessment in a hyperbolic microchannel: the diamide and glutaraldehyde effect. WebmedCentralplus Biomedical Engineering. 1: WMCPLS00253

    Google Scholar 

  23. Sbalzarini IF, Koumoutsakos P (2005) Feature point tracking and trajectory analysis for video imaging in cell biology. J Struct Bio 151(2):182–195

    Article  Google Scholar 

  24. Smith MB, Karatekin E, Gohlke A, Mizuno H, Watanabe N, Vavylonis D (2011) Interactive, computer-assisted tracking of speckle trajectories in fluorescence microscopy: application to actin polymerization and membrane fusion. Biophys J 101:1794–1804

    Article  Google Scholar 

  25. Tomasi C, Manduchi R (1998) Bilateral filtering for gray and color images. International Conference on Computer Vision, pp 839–846

    Google Scholar 

  26. Vincent L, Soille P (1991) Watersheds in digital spaces: an efficient algorithm based on immersion simulations. IEEE PAMI 13(6):583–598

    Article  Google Scholar 

  27. Weiss Y (1997) Smoothness in layers: motion segmentation using nonparametric mixture estimation. Watersheds in digital spaces: An efficient algorithm based on immersion simulations, Int Conf on Computer Vision and Pattern Recognition, pp 520–527

    Google Scholar 

  28. Yaginuma T, Oliveira MS, Lima R, Ishikawa T, Yamaguchi T (2013) Human red blood cell behavior under homogeneous extensional flow in a hyperbolic-shaped microchannel. Biomicrofluidics 7:54110

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the financial support provided by PTDC/SAUBEB/105650/2008, PTDC/SAU-ENB/116929/2010, EXPL/EMS-SIS/2215/2013 from FCT (Science and Technology Foundation), COMPETE, QREN and European Union (FEDER).

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Correspondence to B. Taboada .

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Taboada, B., Monteiro, F., Lima, R. (2015). Tracking Red Blood Cells Flowing through a Microchannel with a Hyperbolic Contraction: An Automatic Method. In: Tavares, J., Natal Jorge, R. (eds) Developments in Medical Image Processing and Computational Vision. Lecture Notes in Computational Vision and Biomechanics, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-13407-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-13407-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13406-2

  • Online ISBN: 978-3-319-13407-9

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