Abstract

Coherent anti-Stokes Raman scattering (CARS) gained a lot of importance in chemical imaging. This is due to the fast image acquisition time, the high spatial resolution, the non-invasiveness, and the molecular sensitivity of this method. By using the single-line CARS in contrast to the multiplex CARS, different signal contributions stemming from resonant and non-resonant light–matter interactions are indistinguishable. Here a numerical method is presented in order to extract more information from univariate CARS images: vibrational composition, morphological information, and contributions from index-of-refraction steps can be separated from single-line CARS images. The image processing algorithm is based on the physical properties of CARS process as reflected in the shape of the intensity histogram of univariate CARS images. Because of this the comparability of individual CARS images recorded with different experimental parameters is achieved. The latter is important for a quantitative evaluation of CARS images.

© 2010 Optical Society of America

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    [PubMed]
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2010 (1)

A. Walter, S. Erdmann, T. Bocklitz, E.-M. Jung, N. Vogler, D. Akimov, B. Dietzek, P. Rösch, E. Kothe, and J. Popp, “Detection of cytochrome distribution via linear and nonlinear Raman spectroscopy,” Analyst (Cambridge, U.K.) 135, 908–917 (2010).
[CrossRef]

2009 (11)

C. Krafft, A. A. Ramoji, C. Bielecki, N. Vogler, T. Meyer, D. Akimov, P. Rösch, M. Schmitt, B. Dietzek, I. Petersen, A. Stallmach, and J. Popp, “A comparative Raman and CARS imaging study of colon tissue,” J. Biophotonics 2, 303–312 (2009).
[CrossRef] [PubMed]

C. Krafft, B. Dietzek, and J. Popp, “Raman and CARS microspectroscopy of cells and tissues,” Analyst (Cambridge, U.K.) 134, 1046–1057 (2009).
[CrossRef]

T. Baldacchini, M. Zimmerley, C.-H. Kuo, E. O. Potma, and R. Zadoyan, “Characterization of microstructures fabricated by two-photon polymerization using coherent anti-Stokes Raman scattering microscopy,” J. Phys. Chem. B 113, 12663–12668 (2009).
[CrossRef] [PubMed]

M. Zimmerley, C.-Y. Lin, D. C. Oertel, J. M. Marsh, J. L. Ward, and E. O. Potma, “Quantitative detection of chemical compounds in human hair with coherent anti-Stokes Raman scattering microscopy,” J. Biomed. Opt. 14, 044019 (2009).
[CrossRef] [PubMed]

G. Bergner, S. Chatzipapadopoulos, D. Akimov, B. Dietzek, D. Malsch, T. Henkel, S. Schlücker, and J. Popp, “Quantitative CARS microscopic detection of analytes and their isotopomers in a two-channel microfluidic chip,” Small 5, 2816–2818 (2009).
[CrossRef] [PubMed]

T. Bocklitz, M. Putsche, C. Stüber, J. Käs, A. Niendorf, P. Rösch, and J. Popp, “A comprehensive study of classification methods for medical diagnosis,” J. Raman Spectrosc. 40, 1759–1765 (2009).
[CrossRef]

T. Dörfer, W. Schumacher, N. Tarcea, M. Schmitt, and J. Popp, “Quantitative mineral analysis using Raman spectroscopy and chemometric techniques,” J. Raman Spectrosc. 10, 10.1002/jrs.2503 (2009).
[CrossRef]

Y. S. Huh, A. J. Chung, and D. Erickson, “Surface enhanced Raman spectroscopy and its application to molecular and cellular analysis,” Microfluid. Nanofluid. 6, 285–297 (2009).
[CrossRef]

B.-S. Yeo, J. Stadler, T. Schmid, R. Zenobi, and W. Zhang, “Tip-enhanced Raman spectroscopy—its status, challenges and future directions,” Chem. Phys. Lett. 472, 1–3 (2009).
[CrossRef]

D. Cialla, R. Siebert, U. Hübner, R. Möller, H. Schneidewind, R. Mattheis, J. Petschulat, A. Tünnermann, T. Pertsch, B. Dietzek, and J. Popp, “Ultrafast plasmon dynamics and evanescent field distribution of reproducible surface-enhanced Raman-scattering substrates,” Anal. Bioanal. Chem. 394, 1811–1818 (2009).
[CrossRef] [PubMed]

D. Akimov, S. Chatzipapadopoulos, T. Meyer, N. Tarcea, B. Dietzek, M. Schmitt, and J. Popp, “Different contrast information obtained from CARS and nonresonant FWM images,” J. Raman Spectrosc. 40, 941–947 (2009).
[CrossRef]

2008 (7)

M. Okuno, H. Kano, P. Leproux, V. Couderc, and H.-o Hamaguchi, “Ultrabroadband multiplex CARS microspectroscopy and imaging using a subnanosecond supercontinuum light source in the deep near infrared,” Opt. Lett. 33, 923–925 (2008).
[CrossRef] [PubMed]

C. Fraley and A. Raftery, mclust: Model-Based Clustering/Normal Mixture Modeling, R package version 3.1-5, 2008.

K. Hering, D. Cialla, K. Ackermann, T. Dörfer, R. Möller, H. Schneidewind, R. Mattheis, W. Fritzsche, P. Rösch, and J. Popp, “SERS: a versatile tool in chemical and biochemical diagnostics,” Anal. Bioanal. Chem. 390, 113–124 (2008).
[CrossRef]

J. N. Anker, W. P. Hall, O. Lyandres, N. C. Shah, J. Zhao, and R. P. V. Duyne, “Biosensing with plasmonic nanosensors,” Nat. Mater. 7, 442–453 (2008).
[CrossRef] [PubMed]

S. Tschierlei, B. Dietzek, M. Karnahl, S. Rau, F. M. MacDonnell, M. Schmitt, and J. Popp, “Resonance Raman studies of photochemical molecular devices for multielectron storage,” J. Raman Spectrosc. 39, 557–559 (2008).
[CrossRef]

T. Meyer, D. Akimov, N. Tarcea, S. Chatzipapadopoulos, G. Muschiolik, J. Kobow, M. Schmitt, and J. Popp, “Three-dimensional molecular mapping of a multiple emulsion by means of CARS microscopy,” J. Phys. Chem. B 112, 1420–1426 (2008).
[CrossRef] [PubMed]

J. Hagmar, C. Brackmann, T. Gustavsson, and A. Enejder, “Image analysis in nonlinear microscopy,” J. Opt. Soc. Am. A 25, 2195–2206 (2008).
[CrossRef]

2007 (5)

M. Müller and A. Zumbusch, “Coherent anti-Stokes Raman scattering microscopy,” ChemPhysChem 8, 2156–2170 (2007).
[CrossRef] [PubMed]

C. Matthäus, T. Chernenko, J. A. Newmark, C. M. Warner, and M. Diem, “Label-free detection of mitochondrial distribution in cells by nonresonant Raman microspectroscopy,” Biophys. J. 93, 668–673 (2007).
[CrossRef] [PubMed]

O. Sklyar, W. Huber, and M. Smith, EBImage: Image Processing and Image Analysis Toolkit for R, R package version 2.2.0, 2007.

D. Gachet, F. Billard, N. Sandeau, and H. Rigneault, “Coherent anti-Stokes Raman scattering (CARS) microscopy imaging at interfaces: evidence of interference effects,” Opt. Express 15, 10408–10420 (2007).
[CrossRef] [PubMed]

R. Bivand, F. Leisch, and M. Mächler, pixmap: Bitmap Images (“Pixel Maps”), R package version 0.4-7, 2007.

2006 (3)

B. von Vacano, W. Wohlleben, and M. Motzkus, “Single-beam CARS spectroscopy applied to low-wavenumber vibrational modes,” J. Raman Spectrosc. 37, 404–410 (2006).
[CrossRef]

H. A. Rinia, M. Bonn, and M. Müller, “Quantitative multiplex CARS spectroscopy in congested spectral regions,” J. Phys. Chem. B 110, 4472–4479 (2006).
[CrossRef] [PubMed]

F. Ganikhanov, C. L. Evans, B. G. Saar, and X. S. Xie, “High-sensitivity vibrational imaging with frequency modulation coherent anti-Stokes Raman scattering (FM CARS) microscopy,” Opt. Lett. 31, 1872–1874 (2006).
[CrossRef] [PubMed]

2005 (2)

R. Maksimenka, B. Dietzek, A. Szeghalmi, T. Siebert, W. Kiefer, and M. Schmitt, “Population dynamics of vibrational modes in stilbene-3 upon photoexcitation to the first excited state,” Chem. Phys. Lett. 408, 37–43 (2005).
[CrossRef]

Nikon Systems Inc., rimage: Image Processing Module for R, R package version 0.5-7, 2005.

2004 (1)

2003 (1)

X. Ma, J. Q. Lu, R. S. Brock, K. M. Jacobs, P. Yang, and X.-H. Hu, “Determination of complex refractive index of polystyrene microspheres from 370 to 1610 nm,” Phys. Med. Biol. 48, 4165–4172 (2003).
[CrossRef]

2002 (5)

M. O. Scully, G. W. Kattawar, R. P. Lucht, T. Opatrny, H. Pilloff, A. Rebane, A. V. Sokolov, and M. S. Zubairy, “FAST CARS: engineering a laser spectroscopic technique for rapid identification of bacterial spores,” Proc. Natl. Acad. Sci. U.S.A. 99, 10994–11001 (2002).
[CrossRef] [PubMed]

J.-X. Cheng, A. Volkmer, and X. S. Xie, “Theoretical and experimental characterization of coherent anti-Stokes Raman scattering microscopy,” J. Opt. Soc. Am. B 19, 1363–1375 (2002).
[CrossRef]

Y. R. Shen, The Principles of Nonlinear Optics (Wiley-Interscience, 2002).

A. Volkmer, L. D. Book, and X. S. Xie, “Time-resolved coherent anti-Stokes Raman scattering microscopy: imaging based on Raman free induction decay,” Appl. Phys. Lett. 80, 1505–1507 (2002).
[CrossRef]

A. S. Haka, K. E. Shafer-Peltier, M. Fitzmaurice, J. Crowe, R. R. Dasari, and M. S. Feld, “Identifying microcalcifications in benign and malignant breast lesions by probing differences in their composition using Raman spectroscopy,” Cancer Res. 62, 5375–5380 (2002).
[PubMed]

2001 (5)

E. Potma, W. P. de Boeij, P. J. van Haastert, and D. A. Wiersma, “Real-time visualization of intracellular hydrodynamics in single living cells,” Proc. Natl. Acad. Sci. U.S.A. 98, 1577–1582 (2001).
[CrossRef] [PubMed]

J.-X. Cheng, A. Volkmer, L. D. Book, and X. S. Xie, “An epi-detected coherent anti-Stokes Raman scattering (E-CARS) microscope with high spectral resolution and high sensitivity,” J. Phys. Chem. B 105, 1277–1280 (2001).
[CrossRef]

J.-X. Cheng, L. D. Book, and X. S. Xie, “Polarization coherent anti-Stokes Raman scattering microscopy,” Opt. Lett. 26, 1341–1343 (2001).
[CrossRef]

A. Volkmer, J.-X. Cheng, and X. Sunney Xie, “Vibrational imaging with high sensitivity via epidetected coherent anti-Stokes Raman scattering microscopy,” Phys. Rev. Lett. 87, 023901 (2001).
[CrossRef]

K. Lan and J. W. Jorgenson, “A hybrid of exponential and Gaussian functions as a simple model of asymmetric chromatographic peaks,” J. Chromatogr. A 915, 1–13 (2001).
[CrossRef] [PubMed]

1999 (1)

A. Zumbusch, G. R. Holtom, and X. S. Xie, “Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering,” Phys. Rev. Lett. 82, 4142–4145 (1999).
[CrossRef]

1997 (1)

M. Schmitt, G. Knopp, A. Materny, and W. Kiefer, “Femtosecond time-resolved coherent anti-stokes Raman scattering for the simultaneous study of ultrafast ground and excited state dynamics: iodine vapour,” Chem. Phys. Lett. 270, 9–15 (1997).
[CrossRef]

1996 (1)

A. Myers, “Resonance Raman intensities and charge-transfer reorganization energies,” Chem. Rev. (Washington, D.C.) 96, 911–926 (1996).
[CrossRef]

1992 (1)

M. S. Jeansonne and J. P. Foley, “Improved equations for calculation of chromatographic figures of merit for ideal and skewed chromatographic peaks,” J. Chromatogr. A 594, 1–8 (1992).
[CrossRef]

1991 (1)

M. S. Jeansonne and J. P. Foley, “Review of the exponentially modified Gaussian (EMG) function since 1983,” J. Chromatogr. Sci. 29, 258–266 (1991).

1989 (1)

M. Frigge, D. C. Hoaglin, and B. Iglewicz, “Some implementations of the boxplot,” Am. Stat. 43, 50–54 (1989).
[CrossRef]

1988 (1)

P. J. Naish and S. Hartwell, “Exponentially modified Gaussian functions—a good model for chromatographic peaks in isocratic HPLC?” Chromatographia 26, 285–296 (1988).
[CrossRef]

1977 (1)

A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum likelihood from incomplete data via the em algorithm,” J. R. Stat. Soc. Ser. B (Methodol.) 39, 1–38 (1977).

1974 (1)

M. D. Levenson and N. Bloembergen, “Dispersion of the nonlinear optical susceptibility tensor in centrosymmetric media,” Phys. Rev. B 10, 4447–4463 (1974).
[CrossRef]

1961 (1)

A. C. Albrecht, “On the theory of Raman intensities,” J. Chem. Phys. 34, 1476–1484 (1961).
[CrossRef]

Ackermann, K.

K. Hering, D. Cialla, K. Ackermann, T. Dörfer, R. Möller, H. Schneidewind, R. Mattheis, W. Fritzsche, P. Rösch, and J. Popp, “SERS: a versatile tool in chemical and biochemical diagnostics,” Anal. Bioanal. Chem. 390, 113–124 (2008).
[CrossRef]

Akimov, D.

A. Walter, S. Erdmann, T. Bocklitz, E.-M. Jung, N. Vogler, D. Akimov, B. Dietzek, P. Rösch, E. Kothe, and J. Popp, “Detection of cytochrome distribution via linear and nonlinear Raman spectroscopy,” Analyst (Cambridge, U.K.) 135, 908–917 (2010).
[CrossRef]

G. Bergner, S. Chatzipapadopoulos, D. Akimov, B. Dietzek, D. Malsch, T. Henkel, S. Schlücker, and J. Popp, “Quantitative CARS microscopic detection of analytes and their isotopomers in a two-channel microfluidic chip,” Small 5, 2816–2818 (2009).
[CrossRef] [PubMed]

C. Krafft, A. A. Ramoji, C. Bielecki, N. Vogler, T. Meyer, D. Akimov, P. Rösch, M. Schmitt, B. Dietzek, I. Petersen, A. Stallmach, and J. Popp, “A comparative Raman and CARS imaging study of colon tissue,” J. Biophotonics 2, 303–312 (2009).
[CrossRef] [PubMed]

D. Akimov, S. Chatzipapadopoulos, T. Meyer, N. Tarcea, B. Dietzek, M. Schmitt, and J. Popp, “Different contrast information obtained from CARS and nonresonant FWM images,” J. Raman Spectrosc. 40, 941–947 (2009).
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[CrossRef]

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[CrossRef]

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[CrossRef]

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[CrossRef]

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T. Baldacchini, M. Zimmerley, C.-H. Kuo, E. O. Potma, and R. Zadoyan, “Characterization of microstructures fabricated by two-photon polymerization using coherent anti-Stokes Raman scattering microscopy,” J. Phys. Chem. B 113, 12663–12668 (2009).
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[CrossRef]

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C. Matthäus, T. Chernenko, J. A. Newmark, C. M. Warner, and M. Diem, “Label-free detection of mitochondrial distribution in cells by nonresonant Raman microspectroscopy,” Biophys. J. 93, 668–673 (2007).
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X. Ma, J. Q. Lu, R. S. Brock, K. M. Jacobs, P. Yang, and X.-H. Hu, “Determination of complex refractive index of polystyrene microspheres from 370 to 1610 nm,” Phys. Med. Biol. 48, 4165–4172 (2003).
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Figures (8)

Fig. 1
Fig. 1

Sketch of CARS setup.

Fig. 2
Fig. 2

CARS image-analysis workflow.

Fig. 3
Fig. 3

(A) Schematic view of a grayscale histogram of a CARS image with contribution from near-edge interferences. Two species in addition to the contribution from the resonant CARS signal are visible. (B) Schematic view of a grayscale histogram of a CARS image without interference effects. Here the resonant CARS signal is apparent as the high-intensity shoulder. The histogram in (A) resembles the situation for polystyrene beads surrounded by air while the histogram in (B) is representative for polystyrene beads in agarose. The non-resonant background is typically more intense than the resonant signal depending on the signal-to-background ratio.

Fig. 4
Fig. 4

(A) Grayscale densities after scaling of resonant CARS images of polystyrene beads. Images were recorded at two different Stokes shifts (2820 and 2860 cm 1 ) for beads embedded in agarose (denoted as + Agar ) and in air (−Agar). An offset of 0.2 was applied for two curves for readability. Note that the peak of the beads in agarose is shifted from 1 due to the big slope at the high-intensity side. (B) Boxplot of the estimated bead sizes of the polystyrene beads in air under resonant conditions. The boxplot [51] describes the statistics of an observation: the upper and lower borders of the box are equal to the lower and upper quartiles, while the bold line in the middle represents the median. The whisker is 1.5 times the interquartile range and can be used to classify outlier. The median diameter of the beads analyzed manually ( 3.75 μ m ) is bigger than the others obtained by automatically recognizing the sizes. It is obvious that the algorithm does not change the bead sizes much: the mean diameter is 2.81 μ m for the raw image and 2.62 μ m for the computed image.

Fig. 5
Fig. 5

Comparison of the densities of the polystyrene CARS images and the corresponding images. (A) The density of the scaled original with two peaks (interference and background) and the scaled original image. (B) Density of interference effects and interference rings in the respectively processed CARS image. The shoulder in the enlarged interference band is an artifact of the background contribution. (C) Density of the resonant signal with the processed CARS image showing the central parts of the beads only.

Fig. 6
Fig. 6

(A) The corrected CARS image of polystyrene beads and (B) its original recorded under resonant conditions. The white box marks the investigated background region. (C) and (D) show enlargements of the selected area visualizing the noise reduction ability of the algorithm.

Fig. 7
Fig. 7

Image series of the polystyrene beads recorded at different Raman shifts covering non-resonance and resonance conditions. (A) The corrected series shows high contrast; non-resonant and resonant images can be easily distinguished by the intensity of the beads, which peaks in the center of the spherical structures. (Referring to the online figure: red indicates high intensities whereas yellow refers to lower intensities.) (B) The original images series where a distinction between the different conditions is more difficult due to the different shades of the background (i.e., shades of blue in the online figure). Note that the series are plotted from the center to both directions.

Fig. 8
Fig. 8

CARS images of HaCaT cells with the white lines indicating the cross sections investigated and the comparison of the different intensity profiles. (A) original image, (B) data correction according to [38], (C) data correction according to the algorithm described herein. The bottom profile shows a good reproduction of the resonant structures indicating the high chemical information, which can be extracted without previous knowledge. In the middle profile more noise is observed due to the mathematical operations performed, and slight deviations of the intensity cut along the white line from the other images are observed. It should be noted that the images are plotted with different color scales: the scale of image A begins with the value of the non-resonant background, while the scale of the correction in image (B) features negative values as start values and the scale of image (C) begins with zero, because the non-resonant background is set to zero.

Equations (6)

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I a s I s I p 2 | χ 1111 ( 3 ) ( ω a s ) | 2 .
χ 1111 ( 3 ) ( ω a s ) = χ NR ( 3 ) + A t ω t 2 ω p i Γ t + A t ω t 2 ω s i Γ t + A t ω t ( ω p + ω s ) i Γ t + R A R ω R ( ω p ω s ) i Γ R ,
χ 1111 ( 3 ) = χ NR ( 3 ) + χ R ( 3 ) = χ NR ( 3 ) + R A R ω R ( ω p ω s ) i Γ R .
π ( d 2 ) 2 = m ( 0.15 μ m ) 2 d = 2 ( 0.15 μ m ) m π ,
μ raw = 1.0370 μ cor = 0.0031 ,
σ raw = 0.1072 σ cor = 0.0680.

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