Abstract

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

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2013 (3)

F. Sadjadi and A. Mahalanobis, “Automatic target recognition XXIII,” Proc. SPIE8744, 358 (2013).

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]

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]

2010 (2)

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]

J. Laurie, D. Wyncoll, and C. Harrison, “New versus old blood - the debate continues,” Crit. Care14(2), 130 (2010).
[CrossRef] [PubMed]

2009 (2)

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]

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]

2008 (2)

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]

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]

2007 (2)

2006 (2)

2005 (4)

2004 (3)

2003 (1)

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]

2001 (1)

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]

2000 (1)

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]

1999 (4)

1996 (1)

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]

1994 (1)

1987 (1)

L. Onural and P. Scott, “Digital decoding of in-line holograms,” Opt. Eng.26(11), 1124–1132 (1987).
[CrossRef]

1967 (1)

J. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett.11(3), 77–79 (1967).
[CrossRef]

1952 (1)

R. Barer, “Interference microscopy and mass determination,” Nature169(4296), 366–367 (1952).
[CrossRef] [PubMed]

Alfieri, D.

Aspert, N.

Barbul, A.

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]

Barer, R.

R. Barer, “Interference microscopy and mass determination,” Nature169(4296), 366–367 (1952).
[CrossRef] [PubMed]

Bevilacqua, F.

Boss, D.

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]

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]

Boulet, V.

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]

Cano, E.

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]

Carapezza, E.

Carl, D.

Charrière, F.

Chesnaud, C.

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]

Colomb, T.

Coppola, G.

Cuche, E.

Daneshpanah, M.

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]

De Nicola, S.

Depeursinge, C.

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]

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]

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]

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]

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]

E. Cuche, F. Bevilacqua, and C. Depeursinge, “Digital holography for quantitative phase-contrast imaging,” Opt. Lett.24(5), 291–293 (1999).
[CrossRef] [PubMed]

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]

Dubois, F.

Emery, Y.

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]

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]

Fairbanks, V.

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]

Ferraro, P.

Finizio, A.

Frauel, Y.

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]

Galland, F.

Goodman, J.

J. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett.11(3), 77–79 (1967).
[CrossRef]

Goudail, F.

Gray, A. D.

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]

Grilli, S.

Harrison, C.

J. Laurie, D. Wyncoll, and C. Harrison, “New versus old blood - the debate continues,” Crit. Care14(2), 130 (2010).
[CrossRef] [PubMed]

Hoyer, J.

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]

Hudgens, R. W.

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]

Javidi, B.

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]

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]

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]

I. Moon and B. Javidi, “Three-dimensional identification of stem cells by computational holographic imaging,” J. R. Soc. Interface4, 305–313 (2007).
[CrossRef] [PubMed]

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]

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]

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]

Jericho, M. H.

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]

Joannes, L.

Jourdain, P.

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]

Kemper, B.

Klee, G.

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]

Korenstein, R.

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]

Kreuzer, H. J.

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]

Kühn, J.

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]

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]

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]

Laurie, J.

J. Laurie, D. Wyncoll, and C. Harrison, “New versus old blood - the debate continues,” Crit. Care14(2), 130 (2010).
[CrossRef] [PubMed]

Lawrence, R.

J. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett.11(3), 77–79 (1967).
[CrossRef]

Legros, J. C.

Lockwood, W. B.

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]

Magistretti, P. J.

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]

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]

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]

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]

Mahalanobis, A.

Marquet, P.

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]

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]

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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).
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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).
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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).
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L. Onural and P. Scott, “Digital decoding of in-line holograms,” Opt. Eng.26(11), 1124–1132 (1987).
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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).
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Yi, F.

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Appl. Opt. (5)

Appl. Phys. Lett. (1)

J. Goodman and R. Lawrence, “Digital image formation from electronically detected holograms,” Appl. Phys. Lett.11(3), 77–79 (1967).
[CrossRef]

Blood Cells Foundation (1)

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]

Crit. Care (1)

J. Laurie, D. Wyncoll, and C. Harrison, “New versus old blood - the debate continues,” Crit. Care14(2), 130 (2010).
[CrossRef] [PubMed]

Cytometry (1)

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]

IEEE Trans. Pattern Anal. Mach. Intell. (1)

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]

J. Biomed. Opt. (3)

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]

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).
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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]

J. Opt. Soc. Am. A (2)

J. R. Soc. Interface (1)

I. Moon and B. Javidi, “Three-dimensional identification of stem cells by computational holographic imaging,” J. R. Soc. Interface4, 305–313 (2007).
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Nature (1)

R. Barer, “Interference microscopy and mass determination,” Nature169(4296), 366–367 (1952).
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Opt. Eng. (2)

L. Onural and P. Scott, “Digital decoding of in-line holograms,” Opt. Eng.26(11), 1124–1132 (1987).
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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]

Opt. Express (3)

Opt. Lett. (4)

Proc. IEEE (2)

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]

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]

Proc. Natl. Acad. Sci. U. S. A. (1)

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]

Proc. SPIE (1)

F. Sadjadi and A. Mahalanobis, “Automatic target recognition XXIII,” Proc. SPIE8744, 358 (2013).

Transfus. Apheresis Sci. (1)

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]

Transfusion (1)

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).
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Other (4)

“Transfusion handbook, summary information for red blood cells,” National Blood Transfusion Committee.

T. Tishko, T. Dmitry, and T. Vladimir, Holographic Microscopy of Phase Microscopic Objects Theory and Practice (World Scientific, 2011).

R. Gonzalez and R. Woods, Digital Imaging Processing (Prentice Hall, 2002).

E. Gose, R. Johnsonbaugh, and S. Jost, Pattern Recognition and Image Analysis (Prentice Hall, 1996).

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Figures (5)

Fig. 1
Fig. 1

Schematic of the off-axis digital holographic microscopy.

Fig. 2
Fig. 2

Original RBC quantitative phase image and corresponding segmentation results. (a), (b), (c), (d), (e) and (f) are RBC’s with 8, 16, 30, 34, 47 and 57 days of storage, respectively, while (g), (h), (i), (j), (k) and (l) are the corresponding segmented images of (a), (b), (c), (d), (e) and (f).

Fig. 3
Fig. 3

Relationship between the mean projected surface areas, mean average phase value and the different storage times. (a) Relationship between the mean projected surface area S ¯ of RBCs and storage time. Square is S ¯ and bar is the standard deviation of S . (b) Relationship between Φ ¯ of RBCs [see Eq. (1)] and storage time. Square is the mean and bar is the standard deviation of Φ ¯ .

Fig. 4
Fig. 4

Relationship between MCV, MCH of RBCs and varied storage time. (a) Relationship between MCV and storage time. Square is the mean and bar is the standard deviation of corpuscular volume. (b) Relationship between MCH of RBCs and storage time. Square represents the mean and bar represents the standard deviation of the corpuscular hemoglobin content.

Fig. 5
Fig. 5

Relationship between MCHSD of RBCs and storage time. Square represents the mean and bar represents the standard deviation of the dry mass surface density.

Tables (1)

Tables Icon

Table 1 Characteristic properties of RBCs with different storage days.

Equations (4)

Equations on this page are rendered with MathJax. Learn more.

Φ= 1 N i=1 N φ i ,S=N p 2 ,
V p 2 λ i N φ i 2π( n rbc n m ) ,
DryMass(DM)= 10λ 2πα S φds = 10λ 2πα ΦS,
MCHSD= MCH S .

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