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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 21, Iss. 20 — Oct. 7, 2013
  • pp: 23985–23996
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Imaging through scattering microfluidic channels by digital holography for information recovery in lab on chip

V. Bianco, M. Paturzo, O. Gennari, A. Finizio, and P. Ferraro  »View Author Affiliations


Optics Express, Vol. 21, Issue 20, pp. 23985-23996 (2013)
http://dx.doi.org/10.1364/OE.21.023985


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Abstract

We tackle the problem of information recovery and imaging through scattering microfluidic chips by means of digital holography (DH). In many cases the chip can become opalescent due to residual deposits settling down the inner channel faces, biofilm formation, scattering particle uptake by the channel cladding or its damaging by corrosive substances, or even by condensing effect on the exterior channels walls. In these cases white-light imaging is severely degraded and no information is obtainable at all about the flowing samples. Here we investigate the problem of counting and estimating velocity of cells flowing inside a scattering chip. Moreover we propose and test a method based on the recording of multiple digital holograms to retrieve improved phase-contrast images despite the strong scattering effect. This method helps, thanks to DH, to recover information which, otherwise, would be completely lost.

© 2013 OSA

1. Introduction

The latest technologies in lab-on-a-chip (LOC) devices have recently experienced an impressive growth, allowing to achieve compact structures at micro-scale that enable to handle samples such as reaction agents, cells, etc [1

1. G. M. Whitesides, “The origins and the future of microfluidics,” Nature 442(7101), 368–373 (2006). [CrossRef] [PubMed]

,2

2. D. Erickson and D. Li, “Integrated microfluidic devices,” Anal. Chim. Acta 507(1), 11–26 (2004). [CrossRef]

]. In this framework, optical microscopy applied to microfluidic devices has become a more and more relevant issue, for observing in real-time the bio-chemical processes in microfluidic channels, counting, speed measurement etc..

Many microscopy techniques, such as bright-field and fluorescence microscopy, phase contrast microscopy, differential interference contrast (DIC) microscopy or laser scanning confocal microscopy, have been developed and applied in last years for the optical imaging in microfluidics [3

3. P. C. H. Li, L. de Camprieu, J. Cai, and M. Sangar, “Transport, retention and fluorescent measurement of single biological cells studied in microfluidic chips,” Lab Chip 4(3), 174–180 (2004). [CrossRef] [PubMed]

8

8. C. Simonnet and A. Groisman, “Two-dimensional hydrodynamic focusing in a simple microfluidic device,” Appl. Phys. Lett. 87(114104), 1–3 (2005).

]. In [9

9. C. E. Willert and M. Gharib, “Digital PIV,” Exp. Fluids 10, 181–193 (1991).

11

11. R. Lima, S. Wada, S. Tanaka, M. Takeda, T. Ishikawa, K. Tsubota, Y. Imai, and T. Yamaguchi, “In vitro blood flow in a rectangular PDMS microchannel: experimental observations using a confocal micro-PIV system,” Biomed. Microdevices 10(2), 153–167 (2008). [CrossRef] [PubMed]

] particle image velocimetry (PIV) has been performed in microfluidic environment. Besides intensity images, also quantitative phase-contrast imaging methods, based on interferometric technique have been developed [12

12. G. Popescu, “Quantitative phase imaging of nanoscale cell structure and dynamics,” Methods Cell Biol. 90, 87–115 (2008). [CrossRef] [PubMed]

,13

13. N. Lue, G. Popescu, T. Ikeda, R. R. Dasari, K. Badizadegan, and M. S. Feld, “Live cell refractometry using microfluidic devices,” Opt. Lett. 31(18), 2759–2761 (2006). [CrossRef] [PubMed]

].

Moreover, recently, especially compact on-chip imaging methods have been developed. For example, a lensless, ultra wide-field cell monitoring array platform based on shadow imaging (LUCAS), has been developed by Ozcan et al. [14

14. A. Ozcan and U. Demirci, “Ultra wide-field lens-free monitoring of cells on-chip,” Lab Chip 8(1), 98–106 (2007). [CrossRef] [PubMed]

16

16. D. Tseng, O. Mudanyali, C. Oztoprak, S. O. Isikman, I. Sencan, O. Yaglidere, and A. Ozcan, “Lensfree microscopy on a cellphone,” Lab Chip 10(14), 1787–1792 (2010). [CrossRef] [PubMed]

]. A different technique consists in a microfluidic-based scanning optical microscope, called optofluidic microscopy (OFM) [17

17. X. Heng, D. Erickson, L. R. Baugh, Z. Yaqoob, P. W. Sternberg, D. Psaltis, and C. Yang, “Optofluidic microscopy--a method for implementing a high resolution optical microscope on a chip,” Lab Chip 6(10), 1274–1276 (2006). [CrossRef] [PubMed]

19

19. G. Zheng, S. A. Lee, S. Yang, and C. Yang, “Sub-pixel resolving optofluidic microscope for on-chip cell imaging,” Lab Chip 10(22), 3125–3129 (2010). [CrossRef] [PubMed]

], where biological samples are delivered in a microfluidic channel and scanned by a linear array of sampling points.

On the other hand, Bishara et al. integrated the LED-based digital in-line holography platform with a microfluidic channel for sample transporting, referred to as holographic optofluidic microscopy (HOM) [20

20. W. Bishara, H. Zhu, and A. Ozcan, “Holographic opto-fluidic microscopy,” Opt. Express 18(26), 27499–27510 (2010). [CrossRef] [PubMed]

22

22. A. Greenbaum, U. Sikora, and A. Ozcan, “Field-portable wide-field microscopy of dense samples using multi-height pixel super-resolution based lensfree imaging,” Lab Chip 12(7), 1242–1245 (2012). [CrossRef] [PubMed]

].

On the other side, digital holography (DH) is a well assessed technique to get added-value information such as qualitative and quantitative phase-contrast microscopy in a large number of applications, e.g. for shape and strain measurements [23

23. M. Hÿtch, F. Houdellier, F. Hüe, and E. Snoeck, “Nanoscale holographic interferometry for strain measurements in electronic devices,” Nature 453(7198), 1086–1089 (2008). [CrossRef] [PubMed]

,24

24. Y. Kikuchi, D. Barada, T. Kiire, and T. Yatagai, “Doppler phase-shifting digital holography and its application to surface shape measurement,” Opt. Lett. 35(10), 1548–1550 (2010). [CrossRef] [PubMed]

], optical-image encryption [25

25. Y. Frauel, A. Castro, T. J. Naughton, and B. Javidi, “Resistance of the double random phase encryption against various attacks,” Opt. Express 15(16), 10253–10265 (2007). [CrossRef] [PubMed]

], quantitative analysis of biological samples [26

26. N. Pavillon, J. Kühn, C. Moratal, P. Jourdain, C. Depeursinge, P. J. Magistretti, and P. Marquet, “Early cell death detection with digital holographic microscopy,” PLoS ONE 7(1), e30912 (2012). [CrossRef] [PubMed]

30

30. J. Rosen and G. Brooker, “Non-scanning motionless fluorescence three-dimensional holographic microscopy,” Nat. Photonics 2(3), 190–195 (2008). [CrossRef]

], 3D imaging and display [31

31. M. Paturzo, P. Memmolo, A. Finizio, R. Näsänen, T. J. Naughton, and P. Ferraro, “Synthesis and display of dynamic holographic 3D scenes with real-world objects,” Opt. Express 18(9), 8806–8815 (2010). [CrossRef] [PubMed]

] using a wide range of experimental setups and light sources [32

32. F. Dubois, L. Joannes, and J. C. Legros, “Improved three-dimensional imaging with digital holography microscope using a partial spatial coherent source,” Appl. Opt. 38(34), 7085–7094 (1999). [CrossRef] [PubMed]

39

39. I. Alexeenko, J. F. Vandenrijt, G. Pedrini, C. Thizy, B. Vollheim, W. Osten, and M. P. Georges, “Nondestructive testing by using long-wave infrared interferometric techniques with CO2 lasers and microbolometer arrays,” Appl. Opt. 52(1), A56–A67 (2013). [CrossRef] [PubMed]

].

Recently, DH has been demonstrated to be a real and simple key solution for imaging in turbid media [27

27. 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(17), 3073–3076 (2012). [CrossRef] [PubMed]

,28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

]. In fact, in case the object of interest is dipped into a turbid channel, both white-light imaging and conventional optics are not suited to extract the useful content of information from the multiple unwanted scattering contributions. Moreover, in many cases the fluid, although initially transparent, gets turbid as a result of chemical processes happening inside the chip. So far, many efforts have been spent to achieve imaging through scattering layers and turbid fluids [17

17. X. Heng, D. Erickson, L. R. Baugh, Z. Yaqoob, P. W. Sternberg, D. Psaltis, and C. Yang, “Optofluidic microscopy--a method for implementing a high resolution optical microscope on a chip,” Lab Chip 6(10), 1274–1276 (2006). [CrossRef] [PubMed]

,18

18. X. Cui, L. M. Lee, X. Heng, W. Zhong, P. W. Sternberg, D. Psaltis, and C. Yang, “Lensless high-resolution on-chip optofluidic microscopes for Caenorhabditis elegans and cell imaging,” Proc. Natl. Acad. Sci. U.S.A. 105(31), 10670–10675 (2008). [CrossRef] [PubMed]

,33

33. Y. Pu, M. Centurion, and D. Psaltis, “Harmonic holography: a new holographic principle,” Appl. Opt. 47(4), A103–A110 (2008). [CrossRef] [PubMed]

] but at the cost of an increasing complexity of the optical set-up [40

40. Z. Yaqoob, D. Psaltis, M. S. Feld, and C. Yang, “Optical phase conjugation for turbidity suppression in biological samples,” Nat. Photonics 2(2), 110–115 (2008). [CrossRef] [PubMed]

].

Recently, fluorescence imaging through rough scattering materials has been studied with good results relying on view angle diversity [41

41. J. Bertolotti, E. G. van Putten, C. Blum, A. Lagendijk, W. L. Vos, and A. P. Mosk, “Non-invasive imaging through opaque scattering layers,” Nature 491(7423), 232–234 (2012). [CrossRef] [PubMed]

]. DH instead can solve the problem of seeing through turbid fluids at micro-scale by a direct and simple approach. In particular, if the medium flows along the channel at sufficient speed, the Doppler effect is useful to get rid of the contributions scattered by the colloidal particles of turbid fluid [27

27. 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(17), 3073–3076 (2012). [CrossRef] [PubMed]

]. Moreover, even in case the flow speed is not enough to take advantage of the Doppler effect, the medium itself provides the solution, as the Brownian motion of the colloidal particles can be exploited to acquire a set of holograms with uncorrelated speckle patterns to be incoherently averaged [28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

,29

29. V. Bianco, M. Paturzo, A. Finizio, P. Ferraro, and P. Memmolo, “Seeing through turbid fluids: a new perspective in microfluidics,” Opt. Photonics News 23(12), 33 (2012). [CrossRef]

].

Nonetheless, in microfluidic experiments another annoying problem can occur whenever a transparent medium flows inside a channel. In fact the flowing liquid could deteriorate the channels walls making them rough or scattering [42

42. Y. Wang, D. Wang, D. Yang, L. Ouyang, J. Zhao, and P. Spozmai, “Microchannel detection of microfluidic chips with digital holography imaging system,” Proc. SPIE 8418, 841816, 841816-6 (2012). [CrossRef]

,43

43. J. Y. Yoon, J. H. Han, B. Heinze, and L. J. Lucas, “Microfluidic device detection of waterborne pathogens through static light scattering of latex immunoagglutination using proximity optical fibers,” Proc. Spie 6556, 65560M (2007). [CrossRef]

]. Or simply, inherently the fabrication process of the chip produces a scattering surface at one of walls of the channels thus preventing imaging in through transmission. In fact, it is usual that residuals of chemical reactions occurring inside the chip settle down the inner channel faces. At the same time, the particle uptake by the channel cladding or its damaging due to corrosive substances could unavoidably degrade the microfluidic chip. More frequently, a simple deposit due to sedimentation of colloids dispersed in the liquid could make the channel internal walls acting as scattering surfaces. Even a vapor condensation can occur on the external channel faces as a function of humidity and temperatures. Besides, an impairing factor for the imaging capabilities in microfluidic devices is due to the presence of bio-films, typically made of bacteria, in which groups of microorganisms stick to each other creating a scattering surface [43

43. J. Y. Yoon, J. H. Han, B. Heinze, and L. J. Lucas, “Microfluidic device detection of waterborne pathogens through static light scattering of latex immunoagglutination using proximity optical fibers,” Proc. Spie 6556, 65560M (2007). [CrossRef]

49

49. S. H. Hong, M. Hegde, J. Kim, X. Wang, A. Jayaraman, and T. K. Wood, “Synthetic quorum-sensing circuit to control consortial biofilm formation and dispersal in a microfluidic device,” Nat. Commun. 3(613), 613 (2012). [CrossRef] [PubMed]

]. Such degradations can occur while the channel is under observation, so that the microfluidic chip cannot be simply replaced. In all these cases, to our best knowledge, no solution has been provided in literature, and such observations cannot be performed at all, impairing the monitoring of phenomena developing over long time periods. This strongly limits the variety of tests which can be performed in microfluidic platforms.

As a consequence, a severe scattering layer will appear onto the internal or external channels' walls, thus impairing the vision by any white-light or coherent laser source based microscope. An example is reported in Fig. 1
Fig. 1 Imaging through scattering microfluidics. (a) White-light image of a microfluidic chip with four channels. A salt deposit is settled only in the second channel (red dashed box), with opacity increasing from left to right. (b) White-light view of a different portion of the chip, with the maximum layer thickness. (c-d) Only the left part of a test target is placed behind a scattering channel imaged respectively by (c) white-light microscopy and (d) coherent laser microscopy at λ = 632,8μm. (e) Coherent laser microscopy of the target in absence of the scattering layer. (f-g) White-light images of the salt deposit inside the chip obtained with (f) 20x and (g) 50x magnification.
, where white-light and optical images of a microfluidic chip with four channels is shown. In particular, in Fig. 1(a) the channel in the red dashed box, after usage has experienced residual deposit of salts thus creating scatterings. As can be clearly observed, the scattering density of the inner channel walls increases from left to right, starting from the inlet port. Therefore the visibility through the channel decreases accordingly and any object behind the channel or flowing along it cannot be clearly imaged, or it is completely occluded. A challenging situation is shown in Fig. 1(b), where we reported the white-light view of a different portion of the chip (red dashed box in Fig. 1(b)). In Fig. 1(b), in fact, the scattering is so strong that visibility is completely lost thus making impossible to retrieve any information of what occurs inside the microfluidic channel. For instance, PIV analysis and cell counting [9

9. C. E. Willert and M. Gharib, “Digital PIV,” Exp. Fluids 10, 181–193 (1991).

11

11. R. Lima, S. Wada, S. Tanaka, M. Takeda, T. Ishikawa, K. Tsubota, Y. Imai, and T. Yamaguchi, “In vitro blood flow in a rectangular PDMS microchannel: experimental observations using a confocal micro-PIV system,” Biomed. Microdevices 10(2), 153–167 (2008). [CrossRef] [PubMed]

], as well as the recovery of morphologically relevant parameters of the flowing particles cannot be achieved.

With the aim to illustrate better the reduced visibility effect, we placed a test resolution chart target behind and across the channel of Fig. 1(b). Figure 1(c) and Fig. 1(d) clearly show that only the left part of the target is visible, that is outside the scattering area when imaged respectively with white-light and coherent laser light at λ=632,8μm. Again, the degrading effect on the imaging due to the scattering layer is apparent and no information can be drawn about the test target, whose microscopy image obtained by a coherent laser source is shown in Fig. 1(e). In Fig. 1(f) and Fig. 1(g) we show two images of the deposit layer acquired by an optical microscope with two different magnifications.

Typically, such degradations could occur after the first usages of the chip, or even during a single process, and often force to use the same chip just once and for a limited amount of time, impairing a clear monitoring of slow processes.

Here we investigate the problem of information recovery from microscopic cells flowing inside a rough scattering channel where a clear vision is impaired if the mere conventional optics are employed. More specifically, we show here that by DH it is possible to detect, count and measure the speed of flowing cells and at same time to recover their intensity and phase-contrast maps, despite the huge scattering effect in the inner channel walls (See Fig. 1(b)). While in [27

27. 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(17), 3073–3076 (2012). [CrossRef] [PubMed]

,28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

] the problem to be tackled was the turbidity of the medium itself, and the targets to be imaged were fixed onto one of the inner channel faces (i.e. the targets were static), in this case the object flows along a channel filled with a transparent liquid, and the degradation is due to the scattering channel walls.

In [27

27. 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(17), 3073–3076 (2012). [CrossRef] [PubMed]

] the problem of imaging through moving turbid fluids has been shown to be solvable thanks to the Doppler frequency shift experienced by the light scattered by the moving colloids. Even in case of quasi-static turbid fluids [28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

], the fluid movement provides temporal de-correlation, so that multiple recordings can be simply averaged to lower the turbidity extent. On the contrary, the contemplated issue requires a different approach to be solved.

In Section 2 we propose a model to account for the presence of the scattering layer at the channel wall and its effect in holographic reconstructions. Then, we show how the intrinsic features of the holographic method can be exploited to obtain good visualization, detectionand the velocity measurement of target cells which would be, otherwise, not recognizable at all by white-light microscopy.

We propose a model which treats the effect of the undesired scattered radiation as a speckle noise [28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

]. Many approaches have been suggested in literature to reduce the speckle in coherent imaging systems, mostly relying on spatial filtering of a single image [50

50. J. Garcia-Sucerquia, J. A. H. Ramírez, and D. V. Prieto, “Reduction of speckle noise in digital holography by using digital image processing,” Optik (Stuttg.) 116(1), 44–48 (2005). [CrossRef]

], or averaging multiple DH reconstructions acquired in time-diversity [51

51. F. Monroy, O. Rincon, Y. M. Torres, and J. Garcia-Sucerquia, “Quantitative assessment of lateral resolution improvement in digital holography,” Opt. Commun. 281(13), 3454–3460 (2008). [CrossRef]

]. Here we exploit the diversity provided by the cell movement, with respect to the scattering surface, with the aim to select a set of holograms in which the speckle patterns are uncorrelated. In fact, during the sample motion different portions of scattering channel contributes to the random interference process on the detector and, after a proper matching of the holographic reconstructions, the proposed processing is in effect nothing else than a temporal integration providing a significant improvement in the final recovered image. Differently from the work by Bertolotti et al. no ad hoc set-up is required to obtain the temporal diversity [41

41. J. Bertolotti, E. G. van Putten, C. Blum, A. Lagendijk, W. L. Vos, and A. P. Mosk, “Non-invasive imaging through opaque scattering layers,” Nature 491(7423), 232–234 (2012). [CrossRef] [PubMed]

] but the time sequence is recorded while the cell flows inside the field of view of the recording device and the scattering process itself offers the solution.

Imaging experiments have been carried out in both clear and scattering channels and the results of the proposed processing are shown in Section 3.

2. Working principle

If target (i.e. the cells) flowing into scattering microfluidic channels are imaged by means of DH, each detector element receives the coherent superposition of M contributions, resulting in the following intensity signal:
I(u,v,t)=|i=1M|Chi(u,v,t)||Oi(u,v,t)|exp{j[Oi(u,v,t)+Chi(u,v,t)]}|2++Ng(u,v,t)+Nch(u,v)=Is(u,v,t)+Ng(u,v,t)+Nch(u,v).
(1)
In (1), Oi(u,v,t) is the i-th complex term of useful signal in the recording plane (u,v) at the time t, whereas Chi(u,v,t) models the i-th scattering contribution due to the turbid channel, which is correlated to the useful signal and varies during the recording period due to the cell motion. Moreover, Ng(u,v,t) represents the additive Gaussian incoherent noise, which is time-varying and extends over the whole image, while we indicated with Nch(u,v) the incoherent scattering contribution due to the turbid channel. Noteworthy, this is static during the acquisition period as it only extends over the background area of the field of view. In case of continuous particles sedimentation (or bio-film growth), we can also foresee the presence of a time-dependent scattering contribution, i.e. we can divide Nch(u,v) in two portions, one of them being time-variable. However, in the most of the cases of interest the deposition process is greatly slower than the cell movement so that we can assume this contribution as static during the cell passage inside the field of view.

Due to the linearity of the Fresnel transform Fr{} [52

52. V. Bianco, M. Paturzo, P. Memmolo, A. Finizio, P. Ferraro, and B. Javidi, “Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography,” Opt. Lett. 38(5), 619–621 (2013). [CrossRef] [PubMed]

54

54. T. Kreis, “Handbook of Holographic Interferometry: Optical and Digital Methods,” 1st ed. (Wiley-VCH, Germany, 2004).

], after numerical focusing we obtain the single-look (SL) image:
CSL(x,y,t)=Fr{I(u,v,t)}Fr{IS(u,v,t)}+Fr{Nch(u,v)},
(2)
where(x,y) denotes the image reconstruction plane and we neglected the additive Gaussian noise for the sake of clarity. In fact, in our case the degradation introduced by Ng is much lower than the degradation due to the channel scattering. However, some algorithms exist, specifically designed for digital holography, which suppress efficiently the Gaussian noise, so that a further improvement can be provided if it is necessary [52

52. V. Bianco, M. Paturzo, P. Memmolo, A. Finizio, P. Ferraro, and B. Javidi, “Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography,” Opt. Lett. 38(5), 619–621 (2013). [CrossRef] [PubMed]

]. In such a case, aftersuppressing the Gaussian noise, the Eq. (2) would not be an approximation anymore. Thanks to the coherence of the laser source employed in DH it is trivial to compensate Fr{Nch(u,v)} in (2) by recording and reconstructing a reference hologram. In fact, this problem can be handled as the typical compensation of the lens aberrations in holographic interferometry [55

55. P. Ferraro, S. De Nicola, A. Finizio, G. Coppola, S. Grilli, C. Magro, and G. Pierattini, “Compensation of the inherent wave front curvature in digital holographic coherent microscopy for quantitative phase-contrast imaging,” Appl. Opt. 42(11), 1938–1946 (2003). [CrossRef] [PubMed]

]. This constitute the first intrinsic advantage of DH with respect to the mere white-light microscopy. Hence, the detection of the specimens behind the scattering layer is achievable, e.g. for cell counting purposes, and measurements of the cell velocity can be performed as well. Unfortunately, in the target area the point-to-point relationship between the hologram of interest and the reference one is lost due to the presence of the cell (whose extent depends on the cell refractive index), acting as sort of lens, so that the correlated channel noise results tobe time variant and cannot be extracted from the former term of Eq. (2). Similarly to [28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

,29

29. V. Bianco, M. Paturzo, A. Finizio, P. Ferraro, and P. Memmolo, “Seeing through turbid fluids: a new perspective in microfluidics,” Opt. Photonics News 23(12), 33 (2012). [CrossRef]

], this can be handled as a speckle multiplicative noise combined to the useful signal, and a numerical processing is required to improve the image quality. Hence, in order to reduce the speckle a time sequence of N holograms can be reconstructed, which are acquired while the sample cell flows through the turbid channel, as sketched in Fig. 2
Fig. 2 Sketch of the experimental set-up. On the right side of the image a phase contrast map is shown of the cell flowing through the scattering channel along the x nominal direction.
. While the cell moves inside the camera field of view, different portions of the turbid channel are responsible for the disturbing scattering and each hologram records a different speckle pattern in the target area. Thus, if properly co-registered, the incoherent combination of their reconstructions returns a multi-look (ML) image with improved quality. In particular, the first image of the time sequence can be selected as a master, acquired at time t = T0, and N-1 slave images can be shifted along the x and y directions in order to match the master image. For each slave image the shifts [Δx^,Δy^] are estimated in order to maximize a correlation coefficient ρ(Δx,Δy), i.e.
Δ^=[Δx^,Δy^]=argmaxΔx,Δy{ρ(Δx,Δy)}==argmaxΔx,Δy{EC˜MASTER(x,y,t=T0)[C˜SLAVE(x,y,t)δ(xΔx,yΔy)]EC˜MASTER(x,y,t=T0)2E[C˜SLAVE(x,y,t)δ(xΔx,yΔy)]2},
(3)
where and respectively denote the Hadamard and the convolution product, E indicates the expectation operator, δ()is the impulse signal and
C˜=|CSL||Fr{Nch}||Fr{IS}|
(4)
constitutes (due to the triangular inequality) an underestimated measure of |Fr{IS}|. Once the vector Δ^ is estimated, the SL amplitude images and the SL phase-contrast maps can be shifted and separately (i.e. incoherently) averaged to get the matrices AML and ΦML, respectively being the ML amplitude and phase-contrast maps:
AML(x,y)=1Nn=1N[C˜n(x,y)δ(x-Δx^n,y-Δy^n)]ΦML(x,y)=1Nn=1N[Φ˜n(x,y)δ(x-Δx^n,y-Δy^n)]
(5)
where we denoted with Φ˜nthe n-th SL phase image obtained after subtracting the reference hologram and, if necessary, after performing the phase unwrapping.

3. Experimental results

In our experiments we let fibroblast cells (line NIH-3T3) in DMEM (Dulbecco's modified eagle medium) cell cultivation medium flow along straight microfluidic channels 200μm thick. This is a case in which the white-light microscopy performs well as no scattering layers obstacle the wavefront propagation. Then, the same experiment has been repeated after drying the cell cultivation medium inside the channel, whose effect is the presence of a rough layer, similarly to what is shown in Fig. 1. In order to test the DH capability of extracting information about the specimen we employed in our experiments a classical Mach-Zehnder interferometer as in [27

27. 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(17), 3073–3076 (2012). [CrossRef] [PubMed]

] and we acquired a time sequence of the sample cell flowing through the channel along a straight trajectory inside the camera field of view (nominal path in the sketch of Fig. 2), so that we can assume that the main flow direction occurs along the x axis. Here the nominal path coincides with the longer channel dimension (i.e. the x axis). However, the following analysis can be extended to the case of particles flowing along a nominal trajectory rotated of a certain angle with respect to the x axis. Possible displacements in the y direction can be recovered as in (3) and rotations of the cells can be compensated as well. Again, possible displacements along the optical axis direction can be compensated taking advantage of DH autofocusing and 3D tracking techniques [56

56. 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(27), 28485–28493 (2012). [CrossRef] [PubMed]

]. In the case of clear channel the only noise contributions due to the acquisition system can be contemplated. Figure 3
Fig. 3 Phase-contrast mapping of a sample cell flowing into a clear microfluidic channel. In the inset the top view is shown.
shows a typical phase-contrast map achievable in this situation. The circular cell shape is clearly imaged and from the side-view it is possible to measure a maximum phase dynamic approaching 4.4rad.

In case of scattering channel, by the numerical analysis of the acquired digital holograms, we can retrieve a set of information, useful for detection and counting aims as well as for amplitude and phase imaging.

3.1 Detection and speed measurements

In case of scattering channel, DH allows the rapid detection of the flowing cells (see Media 1) simply defining inside the field of view of the optical system a detection gate, i.e. an ensemble of neighboring rows where to perform a spatial average, and a threshold for counting purposes. Moreover, a first-cut measure of the cell average velocity is obtainable by selecting a set of average windows displaced at uniform distance along the nominal cell path (the average is performed in order to make the measure less sensitive to the channel noise). In fact, while the cell flows along the channel the derivative of the average phase-contrast exhibits a spiky behavior with time, as plotted in Fig. 4
Fig. 4 Derivative of the average phase-contrast vs. time. An example of mean velocity estimation employing four gates is shown. On the right the scattering channel is sketched showing in green, for each plot, the window where the average is performed.
, where an example of velocity measure employing four gates is shown.

We selected n gates where we measured the average phase derivative, from which we estimated the cell velocity as:
v¯x=1NGijDijΔTij,
(6)
whereDijrepresents the distance between the gate i and the gate j, which is a function of the pixel size, ΔTij are the time intervals in which the cell moves between the gates i and j, measured on the leading edge of the phase derivative plots (see Fig. 4), and the average is performed over a number of gate combinations given by NG=n1. Indeed, after the cell detection the positions where to place the detection windows are determined, and their size affects the accuracy of the measure. We found that a window size of 5 pixel is a good compromise between noise mitigation and accuracy of the measure. Thus, we employed n=45 gates, corresponding to NG=44 velocity measures, and we found an average value v¯x=611.4±2.6[μm/s], in good agreement with the nominal velocity of the flow injected into the channel. Noteworthy, in order to calculate the speed it would be in principle possible to adopt the method described in Section 2 to estimate the displacement vector Δ^. However, relying on the SL phase derivative, the co-registration process can be avoided if velocity measures and cell counting are the only scope of the experiment. Conversely, if measures of cell morphology and thickness are of interest, a ML reconstruction is required to recover the missing phase information.

3.2 Phase-contrast mapping

Figure 5(a)
Fig. 5 Holographic reconstructions of a sample cell flowing into a scattering channel. (a) (Media 1) SL phase-contrast map. (b) ML phase-contrast map.
(Media 1) shows the SL phase-contrast DH reconstruction of the fibroblast cell. The degrading effect due to the rough layer is apparent, even if the diffraction pattern due to the cell shape is of help to recognize the cell location. Indeed, thanks to the DH double exposure approach, the only dynamic scattering corrupts the useful signal in the phase-contrast map. In order to test the proposed ML method, we acquired a time sequence of T = 3.6s, resulting in N = 30 frames carrying uncorrelated speckle patterns. We decimated the sequence at rate RD=1/3 corresponding to N = 10 holograms being processed as previously discussed [28

28. V. Bianco, M. Paturzo, A. Finizio, D. Balduzzi, R. Puglisi, A. Galli, and P. Ferraro, “Clear coherent imaging in turbid microfluidics by multiple holographic acquisitions,” Opt. Lett. 37(20), 4212–4214 (2012). [CrossRef] [PubMed]

]. Figure 5(b) shows the obtained ML phase-contrast map. For a further image enhancement we applied a Lee spatial smoothing filter to both the SL and the ML phase images [57

57. J. S. Lee, L. Jurkevich, P. Dewaele, P. Wambacq, and A. Oosterlinck, “Speckle filtering of synthetic aperture radar images: a review,” Remote Sens. Rev. 8(4), 313–340 (1994). [CrossRef]

]. The channel scattering is much mitigated both in the background and in the sample area as an effect of the ML gain, and the typical circular shape of the cell is recovered. It is worth to consider the typical diffraction pattern surrounding the cell, which does not change during its movement along the x direction, i.e. while the channel noise decorrelates. As a consequence, after the speckle averaging, its contribution becomes more powerful with respect to the channel noise and, in turn, the diffraction pattern becomes more regular and visible. The quality improvement resulting from the speckle reduction is more apparent in the side-views of Fig. 6
Fig. 6 Phase-contrast mapping of a sample cell flowing into a scattering microfluidic channel. A side-view is shown along the columns of the image at fixed row. (a) SL. (b) ML. (c) SL post-filtered. (d) ML post-filtered.
, where the phase maps are represented at different processing stages. In the SL map (Fig. 6(a)) the sudden spikes are an apparent effect of the turbid channel scattering. Conversely, this looks reduced in the ML representation of Fig. 6(b). Since the SL map is rapidly oscillating in space, the spatial smoothing results in a dynamic shortening and the quantitative information gets corrupted. For this reason this kind of spatial averaging is not effective for quantitative phase retrieval if applied to SL images. On the contrary, the spikes are almost totally compensated in the ML case and the spatial filtering returns a phase map in which the maximum phase dynamic is preserved. We measured 3.5rad in the processed image, in good agreement with the one obtained in case of clear channel, while in the SL image this value lowers up to 2.2rad. As a consequence of the noise reduction, the imagesharpness is expected to improve. As a sharpness metric, we measured the image gradient of the SL and ML phase images. The higher gradient, the higher sharpness enhancement. It is remarkable that a gradient improvement of 33.8% can be reached with only N=10 images, so that the overall processing requires a computational time lower than 5.5min (0.2s for each SL phase reconstruction and 35s for each co-registration of 1024x1024 double precision images, depending on the hardware/software features of the machine employed for the scope).

4. Conclusions

In this work, we investigated the issue of recovering by DH the qualitative and quantitative information about specimens flowing inside severe scattering microfluidic channels. The scattering can be due to residual deposits resulting from chemical reactions inside the chip and settling down the inner channel faces during the observation period, salt depositions or bio-film formation.

In these cases neither white-light nor optical laser images can detect the targets due to the channel opalescence. The only exception having some chance to afford the problem is a coherent holographic approach, based on the so called “phase-conjugation” which requires photorefractive crystals as holographic recording medium or SLM, and a very complex optical-setup which is not suitable for lab-on-chip applications [40

40. Z. Yaqoob, D. Psaltis, M. S. Feld, and C. Yang, “Optical phase conjugation for turbidity suppression in biological samples,” Nat. Photonics 2(2), 110–115 (2008). [CrossRef] [PubMed]

]. On the contrary, a simple DH interferometric technique employing a common CCD camera as a recording device and exploiting multiple captures of the object while it moves in the camera field of view can solve and overcome this challenging problem. We proposed a model to account for the disturbing contributions in the DH image formation. Then, the target detection and a first-cut measure of the mean velocity of a circular flowing fibroblast cell has been performed, exploiting SL phase-contrast images. Noteworthy, the SL phase-contrast maps obtained with double exposure DH approach are sufficient to allow velocity measures and cell counting in scattering microfluidic platforms.

However, for quantitative phase microscopy a further processing is required to improve the image quality and get information on morphological parameters. We proposed and tested a method based on the recording and processing of multiple digital holograms to improve the detection and the imaging through the scattering layer of the cells flowing inside the chip. Our experiments show a ML gain in terms of dynamic preservation and sharpness enhancement.

The proposed method is simple and fast as no ad hoc set-up is required to obtain uncorrelated images, and DH seems to be a particularly suited technique to get rid of the channel scattering. However, it is worth to point out that the phase dynamic is not completely restored in the area corresponding to the cell centre, i.e. where the lens effect is stronger. Further experiments have to be carried out to study the extent of this residual degradation and its dependence on the cell thickness and refractive index. Nevertheless, most of information about the cell morphology is recovered. This work moves a step toward the recovering, in case of lab on chip applications, of essential information which would be otherwise lost by any other imaging technique.

Acknowledgments

This work was supported by Progetto Bandiera “La Fabbrica del Futuro” in the framework of the funded project “Plastic lab-on-chips for the optical manipulation of single cells” (PLUS).

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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(27), 28485–28493 (2012). [CrossRef] [PubMed]

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OCIS Codes
(180.0180) Microscopy : Microscopy
(290.0290) Scattering : Scattering
(110.0113) Imaging systems : Imaging through turbid media
(090.1995) Holography : Digital holography

ToC Category:
Microscopy

History
Original Manuscript: June 27, 2013
Revised Manuscript: July 30, 2013
Manuscript Accepted: August 3, 2013
Published: October 1, 2013

Citation
V. Bianco, M. Paturzo, O. Gennari, A. Finizio, and P. Ferraro, "Imaging through scattering microfluidic channels by digital holography for information recovery in lab on chip," Opt. Express 21, 23985-23996 (2013)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-21-20-23985


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References

  1. G. M. Whitesides, “The origins and the future of microfluidics,” Nature442(7101), 368–373 (2006). [CrossRef] [PubMed]
  2. D. Erickson and D. Li, “Integrated microfluidic devices,” Anal. Chim. Acta507(1), 11–26 (2004). [CrossRef]
  3. P. C. H. Li, L. de Camprieu, J. Cai, and M. Sangar, “Transport, retention and fluorescent measurement of single biological cells studied in microfluidic chips,” Lab Chip4(3), 174–180 (2004). [CrossRef] [PubMed]
  4. J. P. Shelby, J. White, K. Ganesan, P. K. Rathod, and D. T. Chiu, “A microfluidic model for single-cell capillary obstruction by Plasmodium falciparum-infected erythrocytes,” Proc. Natl. Acad. Sci. U.S.A.100(25), 14618–14622 (2003). [CrossRef] [PubMed]
  5. Y. Zeng, L. Jiang, W. Zheng, D. Li, S. Yao, and J. Y. Qu, “Quantitative imaging of mixing dynamics in microfluidic droplets using two-photon fluorescence lifetime imaging,” Opt. Lett.36(12), 2236–2238 (2011). [CrossRef] [PubMed]
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  7. R. Yokokawa, S. Takeuchi, T. Kon, M. Nishiura, K. Sutoh, and H. Fujita, “Unidirectional transport of kinesin-coated beads on microtubules oriented in a microfluidic device,” Nano Lett.4(11), 2265–2270 (2004). [CrossRef]
  8. C. Simonnet and A. Groisman, “Two-dimensional hydrodynamic focusing in a simple microfluidic device,” Appl. Phys. Lett.87(114104), 1–3 (2005).
  9. C. E. Willert and M. Gharib, “Digital PIV,” Exp. Fluids10, 181–193 (1991).
  10. J. Westerweel, D. Dabiri, and M. Gharib, “The effect of a discrete window offset on the accuracy of cross-correlation analysis of digital PIV recordings,” Exp. Fluids23(1), 20–28 (1997). [CrossRef]
  11. R. Lima, S. Wada, S. Tanaka, M. Takeda, T. Ishikawa, K. Tsubota, Y. Imai, and T. Yamaguchi, “In vitro blood flow in a rectangular PDMS microchannel: experimental observations using a confocal micro-PIV system,” Biomed. Microdevices10(2), 153–167 (2008). [CrossRef] [PubMed]
  12. G. Popescu, “Quantitative phase imaging of nanoscale cell structure and dynamics,” Methods Cell Biol.90, 87–115 (2008). [CrossRef] [PubMed]
  13. N. Lue, G. Popescu, T. Ikeda, R. R. Dasari, K. Badizadegan, and M. S. Feld, “Live cell refractometry using microfluidic devices,” Opt. Lett.31(18), 2759–2761 (2006). [CrossRef] [PubMed]
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