OSA's Digital Library

Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 25 — Dec. 16, 2013
  • pp: 30947–30957

Automated quantitative analysis of 3D morphology and mean corpuscular hemoglobin in human red blood cells stored in different periods

Inkyu Moon, Faliu Yi, Yeon H. Lee, Bahram Javidi, Daniel Boss, and Pierre Marquet  »View Author Affiliations

Optics Express, Vol. 21, Issue 25, pp. 30947-30957 (2013)

View Full Text Article

Enhanced HTML    Acrobat PDF (1983 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Quantitative phase (QP) images of red blood cells (RBCs), which are obtained by off-axis digital holographic microscopy, can provide quantitative information about three-dimensional (3D) morphology of human RBCs and the characteristic properties such as mean corpuscular hemoglobin (MCH) and MCH surface density (MCHSD). In this paper, we investigate modifications of the 3D morphology and MCH in RBCs induced by the period of storage time for the purpose of classification of RBCs with different periods of storage by using off-axis digital holographic microscopy. The classification of RBCs based on the duration of storage is highly relevant because a long storage of blood before transfusion may alter the functionality of RBCs and, therefore, cause complications in patients. To analyze any changes in the 3D morphology and MCH of RBCs due to storage, we use data sets from RBC samples stored for 8, 13, 16, 23, 27, 30, 34, 37, 40, 47, and 57 days, respectively. The data sets consist of more than 3,300 blood cells in eleven classes, with more than 300 blood cells per class. The classes indicate the storage period of RBCs and are listed in chronological order. Using the RBCs donated by healthy persons, the off-axis digital holographic microscopy reconstructs several quantitative phase images of RBC samples stored for eleven different periods. We employ marker-controlled watershed transform to remove the background in the RBC quantitative phase images obtained by the off-axis digital holographic microscopy. More than 300 single RBCs are extracted from the segmented quantitative phase images for each class. Such a large number of RBC samples enable us to obtain statistical distributions of the characteristic properties of RBCs after a specific period of storage. Experimental results show that the 3D morphology of the RBCs, in contrast to MCH, is essentially related to the aging of the RBCs.

© 2013 Optical Society of America

OCIS Codes
(100.6890) Image processing : Three-dimensional image processing
(170.1530) Medical optics and biotechnology : Cell analysis
(170.3880) Medical optics and biotechnology : Medical and biological imaging
(090.1995) Holography : Digital holography

ToC Category:
Medical Optics and Biotechnology

Original Manuscript: September 23, 2013
Revised Manuscript: December 1, 2013
Manuscript Accepted: December 1, 2013
Published: December 9, 2013

Virtual Issues
Vol. 9, Iss. 2 Virtual Journal for Biomedical Optics

Inkyu Moon, Faliu Yi, Yeon H. Lee, Bahram Javidi, Daniel Boss, and Pierre Marquet, "Automated quantitative analysis of 3D morphology and mean corpuscular hemoglobin in human red blood cells stored in different periods," Opt. Express 21, 30947-30957 (2013)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. J. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett.11(3), 77–79 (1967). [CrossRef]
  2. L. Onural and P. Scott, “Digital decoding of in-line holograms,” Opt. Eng.26(11), 1124–1132 (1987). [CrossRef]
  3. U. Schnars, “Direct phase determination in hologram interferometry with use of digitally recorded holograms,” J. Opt. Soc. Am. A11(7), 2011–2015 (1994). [CrossRef]
  4. D. Carl, B. Kemper, G. Wernicke, and G. von Bally, “Parameter-optimized digital holographic microscope for high-resolution living-cell analysis,” Appl. Opt.43(36), 6536–6544 (2004). [CrossRef] [PubMed]
  5. C. Wagner, W. Osten, and S. Seebacher, “Direct shape measurement by digital wavefront reconstruction and multi-wavelength contouring,” Opt. Eng.39(1), 79–85 (2000). [CrossRef]
  6. Y. Zhang, G. Pedrini, W. Osten, and H. J. Tiziani, “Reconstruction of in-line digital holograms from two intensity measurements,” Opt. Lett.29(15), 1787–1789 (2004). [CrossRef] [PubMed]
  7. Y. Frauel, T. Naughton, O. Matoba, E. Tajahuerce, and B. Javidi, “Three dimensional imaging and processing using computational holographic imaging,” Proc. IEEE94(3), 636–653 (2006). [CrossRef]
  8. M. Paturzo, F. Merola, S. Grilli, S. De Nicola, A. Finizio, and P. Ferraro, “Super-resolution in digital holography by a two-dimensional dynamic phase grating,” Opt. Express16(21), 17107–17118 (2008). [CrossRef] [PubMed]
  9. B. Rappaz, E. Cano, T. Colomb, J. Kühn, C. Depeursinge, V. Simanis, P. J. Magistretti, and P. Marquet, “Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy,” J. Biomed. Opt.14(3), 034049 (2009). [CrossRef] [PubMed]
  10. F. Dubois, L. Joannes, and J. C. Legros, “Improved three-dimensional imaging with a digital holography microscope with a source of partial spatial coherence,” Appl. Opt.38(34), 7085–7094 (1999). [CrossRef] [PubMed]
  11. W. Xu, M. H. Jericho, I. A. Meinertzhagen, and H. J. Kreuzer, “Digital in-line holography for biological applications,” Proc. Natl. Acad. Sci. U. S. A.98(20), 11301–11305 (2001). [CrossRef] [PubMed]
  12. E. Cuche, F. Bevilacqua, and C. Depeursinge, “Digital holography for quantitative phase-contrast imaging,” Opt. Lett.24(5), 291–293 (1999). [CrossRef] [PubMed]
  13. A. Mahalanobis and F. Goudail, “Methods for automatic target recognition by use of electro-optic sensors: introduction to the feature issue,” Appl. Opt.43(2), 207–209 (2004). [CrossRef]
  14. F. Sadjadi and A. Mahalanobis, “Automatic target recognition XXIII,” Proc. SPIE8744, 358 (2013).
  15. D. J. Triulzi and M. H. Yazer, “Clinical studies of the effect of blood storage on patient outcomes,” Transfus. Apheresis Sci.43(1), 95–106 (2010). [CrossRef] [PubMed]
  16. J. Laurie, D. Wyncoll, and C. Harrison, “New versus old blood - the debate continues,” Crit. Care14(2), 130 (2010). [CrossRef] [PubMed]
  17. B. Javidi, I. Moon, S. Yeom, and E. Carapezza, “Three-dimensional imaging and recognition of microorganism using single-exposure on-line (SEOL) digital holography,” Opt. Express13(12), 4492–4506 (2005). [CrossRef] [PubMed]
  18. A. Stern and B. Javidi, “Theoretical analysis of three-dimensional imaging and recognition of micro-organisms with a single-exposure on-line holographic microscope,” J. Opt. Soc. Am. A24, 163–168 (2007). [CrossRef]
  19. I. Moon and B. Javidi, “Three-dimensional identification of stem cells by computational holographic imaging,” J. R. Soc. Interface4, 305–313 (2007). [CrossRef] [PubMed]
  20. I. Moon, M. Daneshpanah, B. Javidi, and A. Stern, “Automated three-dimensional identification and tracking of micro/nanobiological organisms by computational holographic microscopy,” Proc. IEEE97(6), 990–1010 (2009). [CrossRef]
  21. E. Cuche, P. Marquet, and C. Depeursinge, “Simultaneous amplitude and quantitative phase contrast microscopy by numerical reconstruction of Fresnel off-axis holograms,” Appl. Opt.38(34), 6994–7001 (1999). [CrossRef] [PubMed]
  22. T. Colomb, E. Cuche, F. Charrière, J. Kühn, N. Aspert, F. Montfort, P. Marquet, and C. Depeursinge, “Automatic procedure for aberration compensation in digital holographic microscopy and applications to specimen shape compensation,” Appl. Opt.45(5), 851–863 (2006). [CrossRef] [PubMed]
  23. P. Ferraro, S. Grilli, D. Alfieri, S. De Nicola, A. Finizio, G. Pierattini, B. Javidi, G. Coppola, and V. Striano, “Extended focused image in microscopy by digital holography,” Opt. Express13(18), 6738–6749 (2005). [CrossRef] [PubMed]
  24. P. Marquet, B. Rappaz, P. J. Magistretti, E. Cuche, Y. Emery, T. Colomb, and C. Depeursinge, “Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy,” Opt. Lett.30(5), 468–470 (2005). [CrossRef] [PubMed]
  25. C. Chesnaud, P. Réfrégier, and V. Boulet, “Statistical region snake-based segmentation adapted to different physical noise models,” IEEE Trans. Pattern Anal. Mach. Intell.21(11), 1145–1157 (1999). [CrossRef]
  26. F. Galland and P. Réfrégier, “Minimal stochastic complexity snake-based technique adapted to an unknown noise model,” Opt. Lett.30(17), 2239–2241 (2005). [CrossRef] [PubMed]
  27. F. Yi, I. Moon, B. Javidi, D. Boss, and P. Marquet, “Automated segmentation of multiple red blood cells with digital holographic microscopy,” J. Biomed. Opt.18(2), 026006 (2013). [CrossRef] [PubMed]
  28. B. Rappaz, A. Barbul, Y. Emery, R. Korenstein, C. Depeursinge, P. J. Magistretti, and P. Marquet, “Comparative study of human erythrocytes by digital Holographic microscopy, confocal microscopy, and impedance volume analyzer,” Cytometry73A(10), 895–903 (2008). [CrossRef] [PubMed]
  29. T. Tishko, T. Dmitry, and T. Vladimir, Holographic Microscopy of Phase Microscopic Objects Theory and Practice (World Scientific, 2011).
  30. V. Fairbanks, G. Klee, G. Wiseman, J. Hoyer, A. Tefferi, R. Petitt, and M. Silverstein, “Measurement of blood volume and red cell mass: Re-examination of 51Cr and 125I methods,” Blood Cells Foundation22(2), 169–186 (1996). [CrossRef]
  31. D. Boss, J. Kühn, P. Jourdain, C. Depeursinge, P. J. Magistretti, and P. Marquet, “Measurement of absolute cell volume, osmotic membrane water permeability, and refractive index of transmembrane water and solute flux by digital holographic microscopy,” J. Biomed. Opt.18(3), 036007 (2013). [CrossRef] [PubMed]
  32. R. Barer, “Interference microscopy and mass determination,” Nature169(4296), 366–367 (1952). [CrossRef] [PubMed]
  33. R. Gonzalez and R. Woods, Digital Imaging Processing (Prentice Hall, 2002).
  34. E. Gose, R. Johnsonbaugh, and S. Jost, Pattern Recognition and Image Analysis (Prentice Hall, 1996).
  35. W. B. Lockwood, R. W. Hudgens, I. O. Szymanski, R. A. Teno, and A. D. Gray, “Effects of rejuvenation and frozen storage on 42-day-old AS-3 RBCs,” Transfusion43(11), 1527–1532 (2003). [CrossRef] [PubMed]
  36. “Transfusion handbook, summary information for red blood cells,” National Blood Transfusion Committee.

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


Fig. 1 Fig. 2 Fig. 3
Fig. 4 Fig. 5

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited