Abstract

Particle tracking is a fundamental technique for investigating a variety of biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, observing three-dimensional (3D) trajectories of particles is in general a challenging task in classical microscopy owing to the limited imaging depth of field of commercial optical microscopes, which represents a serious drawback for the analysis of time-lapse microscopy image data. Therefore, numerous automated particle-tracking approaches have been developed by many research groups around the world. Recently, digital holography (DH) in microscopy has rapidly gained credit as one of the elective techniques for these applications, mainly due to the uniqueness of the DH to provide a posteriori quantitative multiple refocusing capability and phase-contrast imaging. Starting from this paradigm, a huge amount of 3D holographic tracking approaches have been conceived and investigated for applications in various branches of science, including optofluids, microfluidics, biomedical microscopy, cell mechano-trasduction, and cell migration. Since a wider community of readers could be interested in such a review, i.e., not only scientists working in the fields of optics and photonics but also users of particle-tracking tools, it should be very beneficial to provide a complete review of state-of-the-art holographic 3D particle-tracking methods and their applications in bio-microfluidics.

© 2015 Optical Society of America

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2015 (5)

L. Miccio, P. Memmolo, F. Merola, P. A. Netti, and P. Ferraro, “Red blood cell as an adaptive optofluidic microlens,” Nat. Commun. 6, 6502 (2015).
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F. Merola, P. Memmolo, L. Miccio, V. Bianco, M. Paturzo, and P. Ferraro, “Diagnostic tools for lab-on-chip applications based on coherent imaging microscopy,” Proc. IEEE 103, 192–204 (2015).
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D. Pejchang, S. Coetmellec, G. Grehan, M. Brunel, D. Lebrun, A. Chaari, T. Grosges, and D. Barchiesi, “Recovering the size of nanoparticles by digital in-line holography,” Opt. Express 23, 18351–18660 (2015).
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M. Almonacid, W. W. Ahmed, M. Bussonnier, P. Mailly, T. Betz, R. Voituriez, N. S. Gov, and M. H. Verlhac, “Active diffusion positions the nucleus in mouse oocytes,” Nat. Cell Biol. 17, 470–479 (2015).
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Y. Wu, X. Wu, L. Yao, G. Gréhan, and K. Cen, “Direct measurement of particle size and 3D velocity of a gas-solid pipe flow with digital holographic particle tracking velocimetry,” Appl. Opt. 54, 2514–2523 (2015).
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2014 (19)

Y. Pang, H. Song, J. H. Kim, X. Hou, and W. Cheng, “Optical trapping of individual human immunodeficiency viruses in culture fluid reveals heterogeneity with single-molecule resolution,” Nat. Nanotechnol. 9, 624–630 (2014).
[Crossref]

D. Ott, S. N. Reihani, and L. B. Oddershede, “Simultaneous three-dimensional tracking of individual signals from multi-trap optical tweezers using fast and accurate photodiode detection,” Opt. Express 22, 23661–23672 (2014).
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L. Miccio, P. Memmolo, F. Merola, S. Fusco, V. Embrione, A. Paciello, M. Ventre, P. A. Netti, and P. Ferraro, “Particle tracking by full-field complex wavefront subtraction in digital holography microscopy,” Lab Chip 14, 1129–1134 (2014).
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X. Yu, J. Hong, C. Liu, M. Cross, D. T. Haynie, and M. K. Kim, “Four-dimensional motility tracking of biological cells by digital holographic microscopy,” J. Biomed. Opt. 19, 045001 (2014).
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G. Di Caprio, A. El Mallahi, P. Ferraro, R. Dale, G. Coppola, B. Dale, G. Coppola, and F. Dubois, “4D tracking of clinical seminal samples for quantitative characterization of motility parameters,” Biomed. Opt. Express 5, 690–700 (2014).
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X. Yu, J. Hong, C. Liu, and M. K. Kim, “Review of digital holographic microscopy for three-dimensional profiling and tracking,” Opt. Eng. 53, 112306 (2014).
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T. Latychevskaia and H.-W. Fink, “Holographic time-resolved particle tracking by means of three-dimensional volumetric deconvolution,” Opt. Express 22, 20994–21003 (2014).
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P. Memmolo, L. Miccio, A. Finizio, P. A. Netti, and P. Ferraro, “Holographic tracking of living cells by three-dimensional reconstructed complex wavefronts alignment,” Opt. Lett. 39, 2759–2762 (2014).
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C. Remacha, B. Scott Nickerson, and H. J. Kreuzer, “Tomography by point source digital holographic microscopy,” Appl. Opt. 53, 3520–3527 (2014).
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P. Memmolo, M. Paturzo, B. Javidi, P. A. Netti, and P. Ferraro, “Refocusing criterion via sparsity measurements in digital holography,” Opt. Lett. 39, 4719–4722 (2014).
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W. Yingchun, W. Xuecheng, Y. Jing, W. Zhihua, G. Xiang, Z. Binwu, C. Linghong, Q. Kunzan, G. Gréhan, and C. Kefa, “Wavelet-based depth-of-field extension, accurate autofocusing, and particle pairing for digital inline particle holography,” Appl. Opt. 53, 556–564 (2014).
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N. Chenouard, I. Smal, F. de Chaumont, M. Maška, I. F. Sbalzarini, Y. Gong, J. Cardinale, C. Carthel, S. Coraluppi, M. Winter, A. R. Cohen, W. J. Godinez, K. Rohr, Y. Kalaidzidis, L. Liang, J. Duncan, H. Shen, Y. Xu, K. E. G. Magnusson, J. Jaldén, H. M. Blau, P. Paul-Gilloteaux, P. Roudot, C. Kervrann, F. Waharte, J.-Y. Tinevez, S. L. Shorte, J. Willemse, K. Celler, G. P. van Wezel, H.-W. Dan, Y.-S. Tsai, C. O. de Solórzano, J.-C. Olivo-Marin, and E. Meijering, “Objective comparison of particle tracking methods,” Nat. Methods 11, 281–289 (2014).
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W. Osten, A. Faridian, P. Gao, K. Körner, D. Naik, G. Pedrini, A. K. Singh, M. Takeda, and M. Wilke, “Recent advances in digital holography [Invited],” Appl. Opt. 53, G44–G63 (2014).
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P. Memmolo, V. Bianco, F. Merola, L. Miccio, M. Paturzo, and P. Ferraro, “Breakthroughs in photonics 2013: holographic imaging,” IEEE Photonics J. 6, 1–6 (2014).
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G. Di Caprio, M. A. Ferrara, L. Miccio, F. Merola, P. Memmolo, P. Ferraro, and G. Coppola, “Holographic imaging of unlabelled sperm cells for semen analysis: a review,” J. Biophotonics 9999, 1–11 (2014).

P. Memmolo, L. Miccio, F. Merola, O. Gennari, P. A. Netti, and P. Ferraro, “3D morphometry of red blood cells by digital holography,” Cytometry Part A 85A, 1030–1036 (2014).
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F. Dubois, A. El Mallahi, J. Dohet-Eraly, and C. Yourassowsky, “Refocus criterion for both phase and amplitude objects in digital holographic microscopy,” Opt. Lett. 39, 4286–4289 (2014).
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J. Dohet-Eraly, C. Yourassowsky, and F. Dubois, “Refocusing based on amplitude analysis in color digital holographic microscopy,” Opt. Lett. 39, 1109–1112 (2014).
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C. A. Trujillo and J. Garcia-Sucerquia, “Automatic method for focusing biological specimens in digital lensless holographic microscopy,” Opt. Lett. 39, 2569–2572 (2014).
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2013 (10)

J. Kostencka, T. Kozacki, and K. Liżewski, “Autofocusing method for tilted image plane detection in digital holographic microscopy,” Opt. Commun. 297, 20–26 (2013).
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F. Merola, L. Miccio, P. Memmolo, G. Di Caprio, A. Galli, R. Puglisi, D. Balduzzi, G. Coppola, P. A. Netti, and P. Ferraro, “Digital holography as a method for 3D imaging and estimating biovolume of motile cells,” Lab Chip 13, 4512–4516 (2013).
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Y. Cotte, F. Toy, P. Jourdain, N. Pavillon, D. Boss, P. Magistretti, P. Marquet, and C. Depeursinge, “Marker-free phase nanoscopy,” Nat. Photonics 7, 113–117 (2013).
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H. Zhu, S. O. Isikman, O. Mudanyali, A. Greenbauma, and A. Ozcan, “Optical imaging techniques for point-of-care diagnostics,” Lab Chip 13, 51–67 (2013).
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E. Watanabe, T. Hoshiba, and B. Javidi, “High-precision microscopic phase imaging without phase unwrapping for cancer cell identification,” Opt. Lett. 38, 1319–1321 (2013).
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H. A. İlhan, M. Doğar, and M. Özcan, “Fast autofocusing in digital holography using scaled holograms,” Opt. Commun. 287, 81–84 (2013).
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P. Gao, G. Pedrini, and W. Osten, “Structured illumination for resolution enhancement and autofocusing in digital holographic microscopy,” Opt. Lett. 38, 1328–1330 (2013).
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D. Lebrun, L. Mees, D. Frechou, S. Coetmellec, M. Brunel, and D. Allano, “Long time exposure digital in-line holography for 3-D particle trajectography,” Opt. Express 21, 23522–23530 (2013).
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F. Marsà, A. Farré, E. Martín-Badosa, and M. MontesUsategui, “Holographic optical tweezers combined with back-focal-plane displacement detection,” Opt. Express 21, 30282–30294 (2013).
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Á. Barroso, M. Woerdemann, A. Vollmer, G. von Bally, B. Kemper, and C. Denz, “Three-dimensional exploration and mechano-biophysical analysis of the inner structure of living cells,” Small 9, 885–893 (2013).
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2012 (11)

A. Farré, F. Marsà, and M. Montes-Usategui, “Optimized back-focal-plane interferometry directly measures forces of optically trapped particles,” Opt. Express 20, 12270–12291 (2012).
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T. W. Su, L. Xue, and A. Ozcan, “High-throughput lensfree 3D tracking of human sperms reveals rare statistics of helical trajectories,” Proc. Natl. Acad. Sci. USA 109, 16018–16022 (2012).
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E. Meijering, O. Dzyubachyk, and I. Smal, “Methods for cell and particle tracking,” Methods Enzymol. 504, 183–200 (2012).
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L. Xu, C. C. Aleksoff, and J. Ni, “High-precision three-dimensional shape reconstruction via digital refocusing in multi-wavelength digital holography,” Appl. Opt. 51, 2958–2967 (2012).
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P. Gao, B. Yao, R. Rupp, J. Min, R. Guo, B. Ma, J. Zheng, M. Lei, S. Yan, D. Dan, and T. Ye, “Autofocusing based on wavelength dependence of diffraction in two-wavelength digital holographic microscopy,” Opt. Lett. 37, 1172–1174 (2012).
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J. F. Restrepo and J. Garcia-Sucerquia, “Automatic three-dimensional tracking of particles with high-numerical aperture digital lensless holographic microscopy,” Opt. Lett. 37, 752–754 (2012).
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P. Memmolo, M. Iannone, M. Ventre, P. A. Netti, A. Finizio, M. Paturzo, and P. Ferraro, “On the holographic 3D tracking of in vitro cells characterized by a highly-morphological change,” Opt. Express 20, 28485–28493 (2012).
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F. Merola, L. Miccio, P. Memmolo, M. Paturzo, S. Grilli, and P. Ferraro, “Simultaneous optical manipulation, 3D tracking, and imaging of micro-objects by digital holography in microfluidics,” IEEE Photonics J. 4, 451–454 (2012).
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M. Paturzo, A. Finizio, P. Memmolo, R. Puglisi, D. Balduzzi, A. Galli, and P. Ferraro, “Microscopy imaging and quantitative phase contrast mapping in turbid microfluidic channels by digital holography,” Lab Chip 12, 3073–3076 (2012).
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M. F. Toy, J. Kühn, S. Richard, J. Parent, M. Egli, and C. Depeursinge, “Accelerated autofocusing of off-axis holograms using critical sampling,” Opt. Lett. 37, 5094–5096 (2012).
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P. Gao, B. Yao, J. Min, R. Guo, B. Ma, J. Zheng, M. Lei, S. Yan, D. Dan, and T. Ye, “Autofocusing of digital holographic microscopy based on off-axis illuminations,” Opt. Lett. 37, 3630–3632 (2012).
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2011 (12)

P. Memmolo, G. Di Caprio, C. Distante, M. Paturzo, R. Puglisi, D. Balduzzi, A. Galli, G. Coppola, and P. Ferraro, “Identification of bovine sperm head for morphometry analysis in quantitative phase-contrast holographic microscopy,” Opt. Express 19, 23215–23226 (2011).
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A. El Mallahi and F. Dubois, “Dependency and precision of the refocusing criterion based on amplitude analysis in digital holographic microscopy,” Opt. Express 19, 6684–6698 (2011).
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P. Memmolo, C. Distante, M. Paturzo, A. Finizio, P. Ferraro, and B. Javidi, “Automatic focusing in digital holography and its application to stretched holograms,” Opt. Lett. 36, 1945–1947 (2011).
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K. Dholakia and T. Čižmár, “Shaping the future of manipulation,” Nat. Photonics 5, 335–342 (2011).
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M. Padgett and R. Di Leonardo, “Holographic optical tweezers and their relevance to lab on chip devices,” Lab Chip 11, 1196–1205 (2011).
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Z. Wang, L. Millet, M. Mir, H. Ding, S. Unarunotai, J. Rogers, M. U. Gillette, and G. Popescu, “Spatial light interference microscopy (SLIM),” Opt. Express 19, 1016–1026 (2011).
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P. Memmolo, A. Finizio, M. Paturzo, L. Miccio, and P. Ferraro, “Twin-beams digital holography for 3D tracking and quantitative phase-contrast microscopy in microfluidics,” Opt. Express 19, 25833–25842 (2011).
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L. Dixon, F. C. Cheong, and D. G. Grier, “Holographic deconvolution microscopy for high-resolution particle tracking,” Opt. Express 19, 16410–16417 (2011).
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S. J. Lee, K. W. Seo, Y. S. Choi, and M. H. Sohn, “Three-dimensional motion measurements of free-swimming microorganisms using digital holographic microscopy,” Meas. Sci. Technol. 22, 064004 (2011).
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I. Moon, M. Daneshpanah, A. Anand, and B. Javidi, “Cell identification computational 3-D holographic microscopy,” Opt. Photon. News 22(6), 18–23 (2011).
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A. Guiggiani, B. Torre, A. Contestabile, F. Benfenati, M. Basso, M. Vassalli, and F. Difato, “Long-range and long-term interferometric tracking by static and dynamic force-clamp optical tweezers,” Opt. Express 19, 22364–22376 (2011).
[Crossref]

Y. Wu, X. Wu, Z. Wang, G. Grehan, L. Chen, and K. Cen, “Measurement of microchannel flow with digital holographic microscopy by integrated nearest neighbor and cross-correlation particle pairing,” Appl. Opt. 50, H297–H305 (2011).
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2010 (14)

T. Latychevskaia, F. Gehri, and H.-W. Fink, “Depth-resolved holographic reconstructions by three-dimensional deconvolution,” Opt. Express 18, 22527–22544 (2010).
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O. Otto, F. Czerwinski, J. L. Gornall, G. Stober, L. B. Oddershede, R. Seidel, and U. F. Keyser, “Real-time particle tracking at 10,000 fps using optical fiber illumination,” Opt. Express 18, 22722–22733 (2010).
[Crossref]

S. T. Wereley and C. D. Meinhart, “Recent advances in micro-particle image velocimetry,” Ann. Rev. Fluid Mech. 42, 557–576 (2010).
[Crossref]

J. Katz and J. Sheng, “Applications of holography in fluid mechanics and particle dynamics,” Annu. Rev. Fluid Mech. 42, 531–555 (2010).
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M. Daneshpanah, S. Zwick, F. Schaal, M. Warber, B. Javidi, and W. Osten, “3D holographic imaging and trapping for non-invasive cell identification and tracking,” J. Disp. Technol. 6, 490–499 (2010).
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L. Tian, N. Loomis, J. A. Domínguez-Caballero, and G. Barbastathis, “Quantitative measurement of size and three-dimensional position of fast-moving bubbles in air-water mixture flows using digital holography,” Appl. Opt. 49, 1549–1554 (2010).
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F. C. Cheong, B. J. Krishnatreya, and D. G. Grier, “Strategies for three-dimensional particle tracking with holographic video microscopy,” Opt. Express 18, 13563–13573 (2010).
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M. K. Kim, “Principles and techniques of digital holographic microscopy,” SPIE Rev. 1, 018005 (2010).

M.-K. Kim, “Applications of digital holography in biomedical microscopy,” J. Opt. Soc. Korea 14, 77–89 (2010).
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W. Bishara, H. Zhu, and A. Ozcan, “Holographic opto-fluidic microscopy,” Opt. Express 18, 27499–27510 (2010).
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O. Masihzadeh, P. Schlup, and R. A. Bartels, “Label-free second harmonic generation holographic microscopy of biological specimens,” Opt. Express 18, 9840–9851 (2010).
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S. K. Jericho, P. Klages, J. Nadeau, E. M. Dumas, M. H. Jericho, and H. J. Kreuzer, “In-line digital holographic microscopy for terrestrial and exobiological research,” Planet. Space Sci. 58, 701–705 (2010).
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I. Smal, M. Loog, W. Niessen, and E. Meijering, “Quantitative comparison of spot detection methods in fluorescence microscopy,” IEEE Trans. Med. Imaging 29, 282–301 (2010).
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P. Ruusuvuori, T. Äijö, S. Chowdhury, C. Garmendia-Torres, J. Selinummi, M. Birbaumer, A. M. Dudley, L. Pelkmans, and O. Yli-Harja, “Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images,” BMC Bioinf. 11, 248–264 (2010).
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2009 (9)

W. J. Godinez, M. Lampe, S. Wörz, B. Müller, R. Eils, and K. Rohr, “Deterministic and probabilistic approaches for tracking virus particles in time-lapse fluorescence microscopy image sequences,” Med. Image Anal. 13, 325–342 (2009).
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P. Langehanenberg, L. Ivanova, I. Bernhardt, S. Ketelhut, A. Vollmer, D. Dirksen, G. Georgiev, G. von Bally, and B. Kemper, “Automated three-dimensional tracking of living cells by digital holographic microscopy,” J. Biomed. Opt. 14, 014018 (2009).
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T. Kim and T.-C. Poon, “Autofocusing in optical scanning holography,” Appl. Opt. 48, H153–H159 (2009).
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S. Lee, J. Y. Lee, W. Yang, and D. Y. Kim, “Autofocusing and edge detection schemes in cell volume measurements with quantitative phase microscopy,” Opt. Express 17, 6476–6486 (2009).
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C.-L. Hsieh, R. Grange, Y. Pu, and D. Psaltis, “Three-dimensional harmonic holographic microcopy using nanoparticles as probes for cell imaging,” Opt. Express 17, 2880–2891 (2009).
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F. C. Cheong, B. Sun, R. Dreyfus, A. Grill, K. Xiao, L. Dixon, and D. G. Grier, “Flow visualization and flow cytometry with holographic video microscopy,” Opt. Express 17, 13071–13079 (2009).
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I. Moon, M. Daneshpanah, B. Javidi, and A. Stern, “Automated three-dimensional identification and tracking of micro/nanobiological organisms by computational holographic microscopy,” Proc. IEEE 97, 990–1010 (2009).
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Y.-S. Choi and S.-J. Lee, “Three-dimensional volumetric measurement of red blood cell motion using digital holographic microscopy,” Appl. Opt. 48, 2983–2990 (2009).
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S. Keen, A. Yao, J. Leach, R. Di Leonardo, C. Saunter, G. Love, J. Cooper, and M. Padgett, “Multipoint viscosity measurements in microfluidic channels using optical tweezers,” Lab Chip 9, 2059–2062 (2009).
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2008 (7)

2007 (6)

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A. D. Franck, A. F. Powers, D. R. Gestaut, T. Gonen, T. N. Davis, and C. L. Asbury, “Tension applied through the Dam1 complex promotes microtubule elongation providing a direct mechanism for length control in mitosis,” Nat. Cell. Biol. 9, 832–837 (2007).
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M. Daneshpanah and B. Javidi, “Tracking biological microorganisms in sequence of 3D holographic microscopy images,” Opt. Express 15, 10761–10766 (2007).
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J. Sheng, E. Malkiel, J. Katz, J. Adolf, R. Belas, and A. R. Place, “Digital holographic microscopy reveals prey-induced changes in swimming behavior of predatory dinoflagellates,” Proc. Natl. Acad. Sci. USA 104, 17512–17517 (2007).
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L. Miccio, D. Alfieri, S. Grilli, P. Ferraro, A. Finizio, L. De Petrocellis, and S. D. Nicola, “Direct full compensation of the aberrations in quantitative phase microscopy of thin objects by a single digital hologram,” Appl. Phys. Lett. 90, 041104 (2007).
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Y. Frauel, T. J. Naughton, O. Matoba, E. Tajahuerce, and B. Javidi, “Three-dimensional imaging and processing using computational holographic imaging,” Proc. IEEE 94, 636–653 (2006).
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C. J. Mann, L. Yu, and M. K. Kim, “Movies of cellular and sub-cellular motion by digital holographic microscopy,” Biomed. Eng. Online 5, 21 (2006).
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F. Dubois, C. Yourassowsky, O. Monnom, J.-C. Legros, O. Debeir, P. Van Ham, R. Kiss, and C. Decaestecker, “Digital holographic microscopy for the three-dimensional dynamic analysis of in vitro cancer cell migration,” J. Biomed. Opt. 11, 054032 (2006).
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J. Sheng, E. Malkiel, and J. Katz, “Digital holographic microscope for measuring three-dimensional particle distributions and motions,” Appl. Opt. 45, 3893–3901 (2006).
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K. Dholakia and P. Reece, “Optical micromanipulation takes hold,” Nano Today 1(1), 18–27 (2006).
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A. S. Morlens, J. Gautier, G. Rey, P. Zeitoun, J. P. Caumes, M. Kos-Rosset, H. Merdji, S. Kazamias, K. Casson, and M. Fajardo, “Submicrometer digital in-line holographic microscopy at 32  nm with high-order harmonics,” Opt. Lett. 31, 3095–3097 (2006).
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J. Garcia-Sucerquia, W. Xu, S. K. Jericho, P. Klages, M. H. Jericho, and H. J. Kreuzer, “Digital in-line holographic microscopy,” Appl. Opt. 45, 836–850 (2006).
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F. Dubois, C. Schockaert, N. Callens, and C. Yourassowsky, “Focus plane detection criteria in digital holography microscopy by amplitude analysis,” Opt. Express 14, 5895–5908 (2006).
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2005 (9)

R. Yuste, “Fluorescence microscopy today,” Nat. Methods 2, 902–904 (2005).
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P. Jordan, J. Leach, M. Padgett, P. Blackburn, N. Isaacs, M. Goksör, D. Hanstorp, A. Wright, J. Girkine, and J. Cooper, “Creating permanent 3D arrangements of isolated cells using holographic optical tweezers,” Lab Chip 5, 1224–1228 (2005).
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P. M. Hansen, V. K. Bhatia, N. Harrit, and L. Oddershede, “Expanding the optical trapping range of gold nanoparticles,” Nano Lett. 5, 1937–1942 (2005).
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N. Yamaguchi, B.-S. Chae, L. Zhang, K. L. Kiick, and E. M. Furst, “Rheological characterization of polysaccharide-poly(ethyleneglycol) star copolymer hydrogels,” Biomacromolecules 6, 1931–1940 (2005).
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Y. Pu and H. Meng, “Four-dimensional dynamic flow measurement by holographic particle image velocimetry,” Appl. Opt. 44, 7697–7708 (2005).
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R. J. Adrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39, 159–169 (2005).
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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. Express 13, 4492–4506 (2005).
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C. J. Mann, L. F. Yu, C. M. Lo, and M. K. Kim, “High-resolution quantitative phase-contrast microscopy by digital holography,” Opt. Express 13, 8693–8698 (2005).
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B. C. Carter, G. T. Shubeita, and S. P. Gross, “Tracking single particles: a user-friendly quantitative evaluation,” Phys. Biol. 2, 60–72 (2005).
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2004 (4)

2003 (2)

2002 (3)

F. Pereira and M. Gharib, “Defocusing digital particle image velocimetry and the three-dimensional characterization of two-phase flows,” Meas. Sci. Technol. 13, 683–694 (2002).
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Z. Cheng, P. M. Chaikin, and T. G. Mason, “Light streak tracking of optically trapped thin microdisks,” Phys. Rev. Lett. 89, 108303 (2002).
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K. D. Hinsch, “Holographic particle image velocimetry,” Meas. Sci. Technol. 13, R61–R72 (2002).
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2001 (2)

M. K. Cheezum, W. F. Walker, and W. H. Guilford, “Quantitative comparison of algorithms for tracking single fluorescent particles,” Biophys. J. 81, 2378–2388 (2001).
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L. Paterson, M. P. MacDonald, J. Arlt, W. Sibbett, P. E. Bryant, and K. Dholakia, “Controlled rotation of optically trapped microscopic particles,” Science 292, 912–914 (2001).
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2000 (5)

A. Pralle, P. Keller, E. L. Florin, K. Simons, and J. K. Horber, “Sphingolipid-cholesterol rafts diffuse as small entities in the plasma membrane of mammalian cells,” J. Cell Biol. 148, 997–1008 (2000).
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B. Ovryn, “Three-dimensional forward scattering particle image velocimetry applied to a microscopic field-of-view,” Exp. Fluids 29, S175–S184 (2000).
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B. Javidi and E. Tajahuerce, “Three-dimensional object recognition by use of digital holography,” Opt. Lett. 25, 610–612 (2000).
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Y. Pu and H. Meng, “An advanced off-axis holographic particle image velocimetry (HPIV) system,” Exp. Fluids 29, 184–197 (2000).
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1999 (1)

C. D. Meinhart, S. T. Wereley, and J. G. Santiago, “PIV measurements of a microchannel flow,” Exp. Fluids 27, 414–419 (1999).
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1998 (2)

J. G. Santiago, S. T. Wereley, C. D. Meinhart, D. J. Beebe, and R. J. Adrian, “A micro particle image velocimetry system,” Exp. Fluids 25, 316–319 (1998).
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1997 (2)

J. Westerweel, “Fundamentals of digital particle image velocimetry,” Meas. Sci. Technol. 8, 1379–1392 (1997).
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1996 (1)

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1994 (1)

1992 (1)

A. Ashkin, “Forces of a single-beam gradient laser trap on a dielectric sphere in the ray optics regime,” Biophys. J. 61, 569–582 (1992).
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1989 (1)

1986 (1)

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1984 (1)

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R. J. Adrian, “Twenty years of particle image velocimetry,” Exp. Fluids 39, 159–169 (2005).
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Z. Cheng, P. M. Chaikin, and T. G. Mason, “Light streak tracking of optically trapped thin microdisks,” Phys. Rev. Lett. 89, 108303 (2002).
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G. M. Gibson, J. Leach, S. Keen, A. J. Wright, and M. J. Padgett, “Measuring the accuracy of particle position and force in optical tweezers using high-speed video microscopy,” Opt. Express 16, 14561–14570 (2008).
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A. Guiggiani, B. Torre, A. Contestabile, F. Benfenati, M. Basso, M. Vassalli, and F. Difato, “Long-range and long-term interferometric tracking by static and dynamic force-clamp optical tweezers,” Opt. Express 19, 22364–22376 (2011).
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P. Memmolo, M. Iannone, M. Ventre, P. A. Netti, A. Finizio, M. Paturzo, and P. Ferraro, “On the holographic 3D tracking of in vitro cells characterized by a highly-morphological change,” Opt. Express 20, 28485–28493 (2012).
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S. Lee, J. Y. Lee, W. Yang, and D. Y. Kim, “Autofocusing and edge detection schemes in cell volume measurements with quantitative phase microscopy,” Opt. Express 17, 6476–6486 (2009).
[Crossref]

D. Lebrun, L. Mees, D. Frechou, S. Coetmellec, M. Brunel, and D. Allano, “Long time exposure digital in-line holography for 3-D particle trajectography,” Opt. Express 21, 23522–23530 (2013).
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D. Pejchang, S. Coetmellec, G. Grehan, M. Brunel, D. Lebrun, A. Chaari, T. Grosges, and D. Barchiesi, “Recovering the size of nanoparticles by digital in-line holography,” Opt. Express 23, 18351–18660 (2015).
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F. Dubois, C. Schockaert, N. Callens, and C. Yourassowsky, “Focus plane detection criteria in digital holography microscopy by amplitude analysis,” Opt. Express 14, 5895–5908 (2006).
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A. El Mallahi and F. Dubois, “Dependency and precision of the refocusing criterion based on amplitude analysis in digital holographic microscopy,” Opt. Express 19, 6684–6698 (2011).
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P. Memmolo, G. Di Caprio, C. Distante, M. Paturzo, R. Puglisi, D. Balduzzi, A. Galli, G. Coppola, and P. Ferraro, “Identification of bovine sperm head for morphometry analysis in quantitative phase-contrast holographic microscopy,” Opt. Express 19, 23215–23226 (2011).
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C.-L. Hsieh, R. Grange, Y. Pu, and D. Psaltis, “Three-dimensional harmonic holographic microcopy using nanoparticles as probes for cell imaging,” Opt. Express 17, 2880–2891 (2009).
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O. Masihzadeh, P. Schlup, and R. A. Bartels, “Label-free second harmonic generation holographic microscopy of biological specimens,” Opt. Express 18, 9840–9851 (2010).
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W. Bishara, H. Zhu, and A. Ozcan, “Holographic opto-fluidic microscopy,” Opt. Express 18, 27499–27510 (2010).
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Z. Wang, L. Millet, M. Mir, H. Ding, S. Unarunotai, J. Rogers, M. U. Gillette, and G. Popescu, “Spatial light interference microscopy (SLIM),” Opt. Express 19, 1016–1026 (2011).
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Opt. Lett. (17)

E. Watanabe, T. Hoshiba, and B. Javidi, “High-precision microscopic phase imaging without phase unwrapping for cancer cell identification,” Opt. Lett. 38, 1319–1321 (2013).
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J. Dohet-Eraly, C. Yourassowsky, and F. Dubois, “Refocusing based on amplitude analysis in color digital holographic microscopy,” Opt. Lett. 39, 1109–1112 (2014).
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M. F. Toy, J. Kühn, S. Richard, J. Parent, M. Egli, and C. Depeursinge, “Accelerated autofocusing of off-axis holograms using critical sampling,” Opt. Lett. 37, 5094–5096 (2012).
[Crossref]

C. A. Trujillo and J. Garcia-Sucerquia, “Automatic method for focusing biological specimens in digital lensless holographic microscopy,” Opt. Lett. 39, 2569–2572 (2014).
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P. Memmolo, C. Distante, M. Paturzo, A. Finizio, P. Ferraro, and B. Javidi, “Automatic focusing in digital holography and its application to stretched holograms,” Opt. Lett. 36, 1945–1947 (2011).
[Crossref]

P. Memmolo, M. Paturzo, B. Javidi, P. A. Netti, and P. Ferraro, “Refocusing criterion via sparsity measurements in digital holography,” Opt. Lett. 39, 4719–4722 (2014).
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P. Gao, G. Pedrini, and W. Osten, “Structured illumination for resolution enhancement and autofocusing in digital holographic microscopy,” Opt. Lett. 38, 1328–1330 (2013).
[Crossref]

P. Gao, B. Yao, R. Rupp, J. Min, R. Guo, B. Ma, J. Zheng, M. Lei, S. Yan, D. Dan, and T. Ye, “Autofocusing based on wavelength dependence of diffraction in two-wavelength digital holographic microscopy,” Opt. Lett. 37, 1172–1174 (2012).
[Crossref]

P. Gao, B. Yao, J. Min, R. Guo, B. Ma, J. Zheng, M. Lei, S. Yan, D. Dan, and T. Ye, “Autofocusing of digital holographic microscopy based on off-axis illuminations,” Opt. Lett. 37, 3630–3632 (2012).
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A. S. Morlens, J. Gautier, G. Rey, P. Zeitoun, J. P. Caumes, M. Kos-Rosset, H. Merdji, S. Kazamias, K. Casson, and M. Fajardo, “Submicrometer digital in-line holographic microscopy at 32  nm with high-order harmonics,” Opt. Lett. 31, 3095–3097 (2006).
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P. Memmolo, L. Miccio, A. Finizio, P. A. Netti, and P. Ferraro, “Holographic tracking of living cells by three-dimensional reconstructed complex wavefronts alignment,” Opt. Lett. 39, 2759–2762 (2014).
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Opt. Photon. News (1)

I. Moon, M. Daneshpanah, A. Anand, and B. Javidi, “Cell identification computational 3-D holographic microscopy,” Opt. Photon. News 22(6), 18–23 (2011).
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Phys. Biol. (1)

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Phys. Rev. Lett. (1)

Z. Cheng, P. M. Chaikin, and T. G. Mason, “Light streak tracking of optically trapped thin microdisks,” Phys. Rev. Lett. 89, 108303 (2002).
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Planet. Space Sci. (1)

S. K. Jericho, P. Klages, J. Nadeau, E. M. Dumas, M. H. Jericho, and H. J. Kreuzer, “In-line digital holographic microscopy for terrestrial and exobiological research,” Planet. Space Sci. 58, 701–705 (2010).
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Proc. IEEE (3)

F. Merola, P. Memmolo, L. Miccio, V. Bianco, M. Paturzo, and P. Ferraro, “Diagnostic tools for lab-on-chip applications based on coherent imaging microscopy,” Proc. IEEE 103, 192–204 (2015).
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I. Moon, M. Daneshpanah, B. Javidi, and A. Stern, “Automated three-dimensional identification and tracking of micro/nanobiological organisms by computational holographic microscopy,” Proc. IEEE 97, 990–1010 (2009).
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Proc. Natl. Acad. Sci. USA (2)

J. Sheng, E. Malkiel, J. Katz, J. Adolf, R. Belas, and A. R. Place, “Digital holographic microscopy reveals prey-induced changes in swimming behavior of predatory dinoflagellates,” Proc. Natl. Acad. Sci. USA 104, 17512–17517 (2007).
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T. W. Su, L. Xue, and A. Ozcan, “High-throughput lensfree 3D tracking of human sperms reveals rare statistics of helical trajectories,” Proc. Natl. Acad. Sci. USA 109, 16018–16022 (2012).
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Science (2)

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Small (1)

Á. Barroso, M. Woerdemann, A. Vollmer, G. von Bally, B. Kemper, and C. Denz, “Three-dimensional exploration and mechano-biophysical analysis of the inner structure of living cells,” Small 9, 885–893 (2013).
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SPIE Rev. (1)

M. K. Kim, “Principles and techniques of digital holographic microscopy,” SPIE Rev. 1, 018005 (2010).

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T. Kreis, Handbook of Holographic Interferometry: Optical and Digital Methods (Wiley-VCH, 2004).

N. T. Shaked, Z. Zalevsky, and L. L. Satterwhite, Biomedical Optical Phase Microscopy and Nanoscopy (Academic, 2012).

J. Persson, A. Mölder, S. G. Pettersson, and K. Alm, “Cell motility studies using digital holographic microscopy,” in Microscopy: Science, Technology, Applications and Education, Microscopy Series (Formatex, 2010), Vol. 4, pp. 1063–1072.

R. J. Adrian, “Statistical properties of particle image velocimetry measurements in turbulent flow,” in Laser Anemometry in Fluid Mechanics III (Springer, 1988), pp. 115–129.

E. Dougherty, ed., Mathematical Morphology in Image Processing (CRC Press, 1992).

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Figures (25)

Figure 1
Figure 1

Top three best-performing methods for each performance measure and combination of biological scenario, particle density, and SNR. The cells are color coded according to method number (Table 1). Reprinted by permission from Macmillan Publishers Ltd.: Chenouard et al., Nat. Methods 11, 281–289 (2014) [10]. Copyright 2014.

Figure 2
Figure 2

Particle-tracking methods enveloped from 1981 to 2014. The blue bars count the holographic methods.

Figure 3
Figure 3

(a) Mach–Zehnder interferometer for digital holographic microscopy of transmissive specimen. BS, beamsplitters; L, lenses. (b)–(e) Digital holographic microscopy process (resolution target) (FOV=200μm×150μm, 1024×768 pixels): (b) hologram, with detail shown in inset; (c) angular spectrum, with the yellow circled area pass-filtered for reconstruction; (d) amplitude image; and (e) phase image. Reprinted with permission from [11].

Figure 4
Figure 4

Examples of quantitative phase microscopy by digital holography: (a) resolution target (25μm×25μm, 452×452 pixels); (b) SKOV-3 ovarian cancer cells (60μm×60μm, 404×404 pixels); (c) SKOV-3 ovarian cancer cell (60μm×60μm, 404×404 pixels); (d) red blood cells (50μm×50μm, 404×404 pixels); (e) cheek epithelial cell (60μm×60μm, 404×404 pixels); and (f) quartz crystal of sand (60μm×60μm, 404×404 pixels). Reprinted with permission from [11].

Figure 5
Figure 5

Intensity reconstructions of MG63 osteosarcoma cell line varying the reconstruction distance. In (b) the distance equal to zero indicates the middle plane of the sample volume. Blue arrows indicate cells very close to their focus plane.

Figure 6
Figure 6

Test on algal species. (a) Modulus of the amplitude and (b) intensity of the reconstructed high-pass filtered amplitude at the best-detected focus plane (reconstruction distance d=68μm). (c) Modulus of the refocused amplitude. (d) Unwrapped phase map of the refocused amplitude. (e) Evolution of the criteria MH,d (proposed) and Md (original) as a function of the reconstruction distance d. The curve exhibiting a minimum at d=68μm corresponds to MH,d, while the one with a maximum, at the same d, corresponds to Md. The presence of a maximum for Md shows the phase nature of the object. Scale bar=20μm. Reprinted with permission from [34]. Copyright 2014, Optical Society of America.

Figure 7
Figure 7

Comparison of (a), (c), (d), and (f) defocused and (b) and (e) focused (a)–(c) reconstructed amplitude and (d)–(f) unwrapped phase distributions of investigations of PaTu 8988S cells in the transmission light arrangement. (g) Focus value functions for SPEC, VAR, GRA, and LAP. Notice that the reconstruction distance is indicated by Δb, while the autofocus position is given by ΔbAF. Reprinted with permission from [29]. Copyright 2008, Optical Society of America.

Figure 8
Figure 8

Comparing GI, TC, and energy metrics for the hologram of a mouse’s cell. In (a) we show the values given by the three metrics for different values of reconstruction distance. In (b) we show the amplitude reconstruction, calculated at a distance corresponding to the extreme point of GI (black circles), while in (c) the corresponding phase reconstruction is reported. Reprinted with permission from [40]. Copyright 2014, Optical Society of America.

Figure 9
Figure 9

Reconstructed digital holographic phase image showing the tracking of L929 cells for 14 h: (a) tracking of a cell population; (b) 3D rendering showing the tracking of a single L929 cell. The images were captured and the cells were analyzed at 10%–20% confluence. Scale bar in A represents 50 μm. Reprinted, with permission of Formatex Research Center, from Ref. [49].

Figure 10
Figure 10

Comparison among the maximum phase values [51], the centroid [52], the weighted centroid [53], and the MBF [54]. (a) reports the strongly morphological change of the tracked cell between two subsequent frames. In (b) the color dots indicate the positions estimated using the four methods. The in-focus distance, calculated by the TC method [39,54], is reported on the top of (b). (c) reports the trajectories of the four methods estimated up to 25 frames. (b) and (c) are reprinted with permission from [54]. Copyright 2012, Optical Society of America.

Figure 11
Figure 11

Four major categories of human sperm swimming patterns. (a) Typical pattern. (b) Helical pattern. (c) Hyperactivated pattern. (d) Hyperhelical pattern. The inset in each panel represents the front view of the straightened trajectory of the sperm. The arrows indicate the directions of the sperms’ forward movement. The time position of each track point is encoded by its color (see the color bar). The helices shown in (b) and (d) are both right-handed. Reprinted with permission from Su et al., Proc. Natl. Acad. Sci. USA 109, 16018–16022 (2012) [95].

Figure 12
Figure 12

Multiple sperm cell tracking. (a) Transversal and (b) reconstructed three-dimensional path. Scale bar is 20 μm; data were acquired over is 11 s. Reprinted with permission from [96]. Copyright 2014, Optical Society of America.

Figure 13
Figure 13

Lorenz–Mie particle tracking and characterization. The upper image is the normalized hologram of a 1.51 μm diameter polystyrene sphere in water. The lower image is a fit to the Lorenz–Mie theory. The solid curve is the azimuthal average of the measured intensity around the center identified by the fit. Dashed curves indicate the azimuthal standard deviation of the hologram’s values, and indicate the measurement error. Plot points show the corresponding radial profiles of the fit. Error bars on the fit values are smaller than the plot symbols. Reprinted with permission from [101]. Copyright 2010, Optical Society of America.

Figure 14
Figure 14

3D tracking results by using Rayleigh–Sommerfeld backpropagation. (a) Volumetric reconstruction of the scattered intensity due to a single colloidal sphere, colored by intensity. (b) Volumetric reconstructions of 22 individual 1.58 μm diameter silica spheres organized in body center crystalline lattice with holographic optical tweezers in distilled water. Reprinted with permission from [101]. Copyright 2010, Optical Society of America.

Figure 15
Figure 15

Comparison of Lorenz–Mie and Rayleigh–Sommerfeld particle-tracking algorithms. (a) Trajectory of a colloidal silica sphere at 1/30 s intervals obtained with the two strategies. Each point indicates the position of the sphere in one holographic snapshot as estimated by the Lorenz–Mie (LM) and Rayleigh–Sommerfeld (RS) approaches. (b) Distribution of differences Δx and Δy in the in-plane position estimated by the two strategies. (c) Mean difference in the axial position as a function of the Lorenz–Mie estimate, obtained from 10,000 measurements. (d) Mean difference in axial position as a function of sphere radius for polystyrene (PS) spheres (circles) and silica (SiO2) spheres (squares). Solid curves are predictions of Lorenz–Mie theory. Reprinted with permission from [101]. Copyright 2010, Optical Society of America.

Figure 16
Figure 16

Three successive holograms out of the sequence and their three-dimensional reconstruction before and after applying the three-dimensional volumetric deconvolution are shown. The area of the reconstructed volume amounts to 625μm×626μm×6000μm. Reprinted with permission from [102]. Copyright 2014, Optical Society of America.

Figure 17
Figure 17

Twin-beam DHM for 3D particle tracking. (a) Illustration of the optical arrangement, (b) simulated interference between two laser beams, and (c) three frames from a recorded sequence of the optical axis motion of a particle. Each subfigure is reprinted with permission from [103]. Copyright 2011, Optical Society of America.

Figure 18
Figure 18

Recording sequence of random motion of particles highlighted by green, blue, and red circles, and the corresponding 3D trajectories. Adapted from Ref. [103].

Figure 19
Figure 19

(a), (b) Two subsequent QPMs of motile cell. In (c) their superimposition has been reported [the red and the green cells are the same in (a) and (b), respectively], and in the upper part the initial values of the ECC and the initial displacements are shown. In (d) the final output of ECC maximization with the corresponding ECC value (top) and final displacements (top right) is shown. (e) Comparison of 3D positions of cell calculated by ECC maximization (blue line) and classical approach (TC+WC) (cyan line). (f) In the top, a QPM with three cells, and in the bottom, the corresponding trajectories. The blue line in (b) is the same as in (a). All displacement units are expressed in micrometers. Adapted from Ref. [104].

Figure 20
Figure 20

Recording microtubule dynamics with tension applied by an optical trapping-based force clamp. (a) Schematic showing experimental geometry and force clamp operation. A polystyrene bead (blue) is held by an optical trap (orange). Dam1 complex (green) on the bead surface mediates attachment to the tip of a dynamic microtubule (red). A portion of the microtubule (dark red) is anchored to the coverslip. As the microtubule grows and shortens, the coverslip is moved via computer to keep a fixed separation (Δx) between the bead and trap, thereby maintaining a constant level of tension. (b) Three (of N=298) representative records showing position against time for tip-attached beads under tension. Increasing position represents bead movement away from the anchored portion of the filament during microtubule. Reprinted by permission from Macmillan Publishers Ltd.: Franck et al., Nat. Cell. Biol. 9, 832–837 (2007) [110]. Copyright 2007.

Figure 21
Figure 21

(a), (b) White light images and (c), (d) DH in microscopy phase images of the PaTu 8988T cell. Particle A is moved in the lateral y direction. (e) Cross sections along the continuous red line and dashed green line, respectively, through the phase images in (c) and (d). The dynamic lateral tracking of the particle that is obtained from the spatial coordinates of the point with maximum phase contrast in the phase images is illustrated in (b). (f) 3D trajectory of the particle obtained by combining the lateral and axial trajectories. Á. Barroso et al., Small 9, 885–893 (2013). [129]. Copyright Wiley-VCH Verlag GmbH & Co. KGaA. Reproduced with permission.

Figure 22
Figure 22

(a) Schematic drawing of the intrinsic lateral shear for a micro-bead illuminated by coherent light. (b) ΔW calculated for two trapped micro-beads. (c)–(e) show QPIs of trapped beads, beads approaching a cell, and beads attached on the cell surface. Adapted with permission of the Royal Society of Chemistry from Ref. [130].

Figure 23
Figure 23

Transversal displacements of (a) left and (b) right beads trapped by the HOT in Fig. 22(c). Transversal displacements of (c) left and (d) right beads corresponding to Fig. 22(e). (e) Horizontal displacement of the bead in (d) versus time. Reproduced from Ref. [130] with permission from the Royal Society of Chemistry.

Figure 24
Figure 24

Vortex shedding cycle recorded and reconstructed by holographic PIV. The vortex structures are represented by the vorticity isosurface at suitable threshold. Reprinted with permission from [144]. Copyright 2005, Optical Society of America.

Figure 25
Figure 25

3D velocity results by Wu et al. (a) 3D position and velocity, (b) velocity distribution, and (c) velocity distribution along the radial direction in the pipe. Reprinted with permission from [146]. Copyright 2015, Optical Society of America.

Tables (1)

Tables Icon

Table 1. List of Participants and their Methods of the Comparison Study Reported in [10]a

Equations (12)

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

O(x,y,z=d)=F1{F{O(x,y,z=0)}×exp[iπλd(v2+μ2)]}.
Md=x,yId(x,y).
SPEC=v,μlog{1+FF{Id}(v,μ)},
VAR=1NxNyx,y[Id(x,y)Id]2,
GRA=x=1Nx1y=1Ny1[Id(x,y)Id(x1,y)]2+[Id(x,y)Id(x,y1)]2,
LAP=x=1Nx1y=1Ny1[Id(x+1,y)+Id(x1,y)+Id(x,y+1)+Id(x,y1)4Id(x,y)]2.
TC=σ{Id}Id,
GI=12k=1Nid[k]od1(Nk+0.5N),
ECC{A,B}=Re{a¯tb¯*a¯b¯},
Δpopt=argmaxECC{Ck,T(Ck+1,Δp)}pk+1=pk+Δpopt,
arg{Wk+1/Wk}=ΔWa1X+a2Y+a3.
Δxk=a1R;Δyk=a2R.

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