Abstract

Mid-infrared hyperspectral imaging has in the past decade emerged as a promising tool for medical diagnostics. In this work, nonlinear frequency upconversion based hyperspectral imaging in the 6 to 8 µm spectral range is presented for the first time, using both broadband globar and narrowband quantum cascade laser illumination. AgGaS2 is used as the nonlinear medium for sum frequency generation using a 1064 nm mixing laser. Angular scanning of the nonlinear crystal provides broad spectral coverage at every spatial position in the image. This study demonstrates the retrieval of series of monochromatic images acquired by a silicon based CCD camera, using both broadband and narrowband illumination and a comparison is made between the two illumination sources for hyperspectral imaging.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2017 (3)

2016 (5)

2015 (1)

2012 (5)

2011 (1)

B. Van Eerdenbrugh and L. S. Taylor, “Application of mid-IR spectroscopy for the characterization of pharmaceutical systems,” Int. J. Pharm. 417(1-2), 3–16 (2011).
[Crossref] [PubMed]

2010 (1)

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

2005 (1)

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

2002 (1)

A. Rogalski, “Infrared detectors: an overview,” Infrared Phys. Technol. 43(3-5), 187–210 (2002).
[Crossref]

1972 (1)

J. Falk and W. B. Tiffany, “Theory of parametric upconversion of thermal images,” J. Appl. Phys. 43(9), 3762–3769 (1972).
[Crossref]

1968 (1)

J. Midwinter, “Image conversion from 1.6µm to the visible in lithium niobate,” Appl. Phys. Lett. 13(3), 68–70 (1968).
[Crossref]

Aleksandrova, A.

Amrania, H.

Andersen, H. V.

Antonacci, G.

Bara, J.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Bhargava, R.

R. Bhargava, “Infrared spectroscopic imaging: the next generation,” Appl. Spectrosc. 66(10), 1091–1120 (2012).
[Crossref] [PubMed]

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

Buse, K.

Capmany, J.

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR image upconversion under dual-wavelength laser illumination,” IEEE Photonics J. 8(6), 6901308 (2016).
[Crossref]

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR Image upconversion using band-limited ASE illumination fiber sources,” Opt. Express 24(8), 8581–8593 (2016).
[Crossref] [PubMed]

Chan, C. H.

Chashnikova, M.

Dam, J. S.

Drummond, L.

Falk, J.

J. Falk and W. B. Tiffany, “Theory of parametric upconversion of thermal images,” J. Appl. Phys. 43(9), 3762–3769 (1972).
[Crossref]

Fedosenko, O.

Fernandez, D. C.

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

Flores, Y.

Forgue-Lafitte, M. E.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Gobinet, C.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Gruska, B.

Hermes, M.

J. Nallala, G. R. Lloyd, M. Hermes, and N. Shepherd, “Enhanced spectral histology in the colon using high-magnification benchtop FTIR imaging,” Vib. Spectrosc. 2610, 83 (2016).

Hewitt, S. M.

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

Høgstedt, L.

Huot, L.

Jeannesson, P.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Junaid, S.

S. Junaid, P. Tidemand-Lichtenberg, and C. Pedersen, “Upconversion based spectral imaging in 6 to 8µm spectral regime,” Proc. SPIE 10088, 100880I (2017).
[Crossref]

Kehlet, L. M.

Kiessling, J.

Kischkat, J.

Klinkmüller, M.

Kühnemann, F.

Kunz, M.

Leick, L.

Levin, I. W.

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

Lloyd, G. R.

J. Nallala, G. R. Lloyd, M. Hermes, and N. Shepherd, “Enhanced spectral histology in the colon using high-magnification benchtop FTIR imaging,” Vib. Spectrosc. 2610, 83 (2016).

Machulik, S.

Maestre, H.

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR image upconversion under dual-wavelength laser illumination,” IEEE Photonics J. 8(6), 6901308 (2016).
[Crossref]

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR Image upconversion using band-limited ASE illumination fiber sources,” Opt. Express 24(8), 8581–8593 (2016).
[Crossref] [PubMed]

Manfait, M.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Mathez, M.

Midwinter, J.

J. Midwinter, “Image conversion from 1.6µm to the visible in lithium niobate,” Appl. Phys. Lett. 13(3), 68–70 (1968).
[Crossref]

Monastyrskyi, G.

Moselund, P. M.

Nallala, J.

J. Nallala, G. R. Lloyd, M. Hermes, and N. Shepherd, “Enhanced spectral histology in the colon using high-magnification benchtop FTIR imaging,” Vib. Spectrosc. 2610, 83 (2016).

Otto, W. R.

Pedersen, C.

Peters, S.

Phillips, C.

Piot, O.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Popko, G.

Rodrigo, P. J.

Rogalski, A.

A. Rogalski, “Infrared detectors: an overview,” Infrared Phys. Technol. 43(3-5), 187–210 (2002).
[Crossref]

Semtsiv, M.

Shepherd, N.

J. Nallala, G. R. Lloyd, M. Hermes, and N. Shepherd, “Enhanced spectral histology in the colon using high-magnification benchtop FTIR imaging,” Vib. Spectrosc. 2610, 83 (2016).

Taylor, L. S.

B. Van Eerdenbrugh and L. S. Taylor, “Application of mid-IR spectroscopy for the characterization of pharmaceutical systems,” Int. J. Pharm. 417(1-2), 3–16 (2011).
[Crossref] [PubMed]

Ted Masselink, W.

Tidemand-Lichtenberg, P.

Tiffany, W. B.

J. Falk and W. B. Tiffany, “Theory of parametric upconversion of thermal images,” J. Appl. Phys. 43(9), 3762–3769 (1972).
[Crossref]

Torregrosa, A. J.

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR Image upconversion using band-limited ASE illumination fiber sources,” Opt. Express 24(8), 8581–8593 (2016).
[Crossref] [PubMed]

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR image upconversion under dual-wavelength laser illumination,” IEEE Photonics J. 8(6), 6901308 (2016).
[Crossref]

Travo, A.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Van Eerdenbrugh, B.

B. Van Eerdenbrugh and L. S. Taylor, “Application of mid-IR spectroscopy for the characterization of pharmaceutical systems,” Int. J. Pharm. 417(1-2), 3–16 (2011).
[Crossref] [PubMed]

Wolf, S.

Wolthuis, R.

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

Wright, N. A.

Appl. Opt. (1)

Appl. Phys. Lett. (1)

J. Midwinter, “Image conversion from 1.6µm to the visible in lithium niobate,” Appl. Phys. Lett. 13(3), 68–70 (1968).
[Crossref]

Appl. Spectrosc. (1)

Histopathology (1)

A. Travo, O. Piot, R. Wolthuis, C. Gobinet, M. Manfait, J. Bara, M. E. Forgue-Lafitte, and P. Jeannesson, “IR spectral imaging of secreted mucus: a promising new tool for the histopathological recognition of human colonic adenocarcinomas,” Histopathology 56(7), 921–931 (2010).
[Crossref] [PubMed]

IEEE Photonics J. (1)

H. Maestre, A. J. Torregrosa, and J. Capmany, “IR image upconversion under dual-wavelength laser illumination,” IEEE Photonics J. 8(6), 6901308 (2016).
[Crossref]

Infrared Phys. Technol. (1)

A. Rogalski, “Infrared detectors: an overview,” Infrared Phys. Technol. 43(3-5), 187–210 (2002).
[Crossref]

Int. J. Pharm. (1)

B. Van Eerdenbrugh and L. S. Taylor, “Application of mid-IR spectroscopy for the characterization of pharmaceutical systems,” Int. J. Pharm. 417(1-2), 3–16 (2011).
[Crossref] [PubMed]

J. Appl. Phys. (1)

J. Falk and W. B. Tiffany, “Theory of parametric upconversion of thermal images,” J. Appl. Phys. 43(9), 3762–3769 (1972).
[Crossref]

J. Opt. Soc. Am. B (1)

Nat. Biotechnol. (1)

D. C. Fernandez, R. Bhargava, S. M. Hewitt, and I. W. Levin, “Infrared spectroscopic imaging for histopathologic recognition,” Nat. Biotechnol. 23(4), 469–474 (2005).
[Crossref] [PubMed]

Nat. Photonics (1)

J. S. Dam, P. Tidemand-Lichtenberg, and C. Pedersen, “Room-temperature mid-infrared single-photon spectral imaging,” Nat. Photonics 6(11), 788–793 (2012).
[Crossref]

Opt. Express (4)

Opt. Lett. (3)

Proc. SPIE (1)

S. Junaid, P. Tidemand-Lichtenberg, and C. Pedersen, “Upconversion based spectral imaging in 6 to 8µm spectral regime,” Proc. SPIE 10088, 100880I (2017).
[Crossref]

Vib. Spectrosc. (1)

J. Nallala, G. R. Lloyd, M. Hermes, and N. Shepherd, “Enhanced spectral histology in the colon using high-magnification benchtop FTIR imaging,” Vib. Spectrosc. 2610, 83 (2016).

Other (1)

F. Penaranda, V. Naranjo, L. Kastl, B. Kemper, G. R. Lloyd, J. Nallala, N. Stone, and J. Schnekenberger, “Multivariate classification of fourier transform infrared hyperspectral images of skin cancer cells,” in proceedings of IEEE European Signal Processing Conference (IEEE, 2016), pp. 1328–1332.
[Crossref]

Supplementary Material (5)

NameDescription
» Visualization 1       series of Upconverted images with varrying phase matching condition, using a globar as illumination source and polystyrene spectral features
» Visualization 2       series of Upconverted images with varrying phase matching condition, using a globar as illumination source and polystyrene spectral features and USAF resolution target
» Visualization 3       Series of upconversion based monochromatic images with polystyrene absorption features
» Visualization 4       series of upconverted images with varrying phase matching condition, using QCL as illumination source
» Visualization 5       series of upconverted images with spectral tuning of the illumination source, i.e. QCL

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Figures (7)

Fig. 1
Fig. 1 Single-pass upconversion system using globar/QCL as illumination sources and a 1064 nm laser as mixing field for sum frequency generation. Zinc Selenide (ZnSe2) lenses are used for the MIR signal, where f1 and f2 can be applied for object magnification, f3 ( = 50 mm) is used to focus the object light into the nonlinear crystal for non-collinear upconversion and provides with f4 ( = 60 mm) a 4f-imaging system with the nonlinear conversion occurring in the Fourier plane. Filters (short pass 1000, long pass 900) and a mirror is used to eliminate the residual pump and stray light from the upconverted signal. An IDS Silicon camera is used for the image acquisition. A clear optical path USAF resolution target and/or polystyrene film (not shown) is used as an object.
Fig. 2
Fig. 2 Upconverted images at 3° crystal rotation (with respect to ĉ-axis) using 500 ms camera integration time (the scale bar refers to the object plane (a) Upconverted image without any sample with full field of view, (b) with PS film showing the absorption line at 6.7 µm. (c) Upconverted images of USAF resolution target and PS film, (d) magnification of 6.667 (100/15) is applied to resolve the smallest features of the resolution target i.e. 35 µm.
Fig. 3
Fig. 3 (a) Simulated Sin c 2 - function intensity distribution at 6.9 µm while rotating the crystal from 0° to 10° in steps of 0.5°. Dashed line shows the summation of all the intensity distribution within the full field of view, (b) 2D response function used for monochromatic image acquisition algorithm,, at wavelength 6 µm and crystal rotation angle 10°.
Fig. 4
Fig. 4 Monochromatic images of USAF resolution target combined with PS film containing both spatial and spectral features acquired by upconversion and post-processing of broadband illuminated target. (a) at 6.5 µm and (b) 6.7 µm wavelength.
Fig. 5
Fig. 5 Measured transmission spectra of polystyrene (a) comparing the FTIR measurement with the upconversion (b) comparison of the spectral resolution depending on the position of the images based on upconversion. It can be noticed that the spectral resolution deteriorates along radial direction
Fig. 6
Fig. 6 Spectral tuning range of QCL measured with cooled MCT detector at 0 and 50 cm distance away from the laser cavity window. Water absorption lines can be noted in the red curve which corresponds to 50 cm distance from the laser cavity window.
Fig. 7
Fig. 7 Upconverted images (a) at 6 µm with magnification (18.75 times), with crystal rotated at 11.05 ° with camera integration time 10 ms, 1.5 W of pump power (b) with resolution target (c, e) Monochromatic (post processed) image of the smallest spatial features (14.25 lines/mm) of USAF resolution target at off resonance, and (d) on resonance of water absorption line.

Equations (6)

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

{ Upconverted image intensity at crystal rotation angle θ i }= I up ( θ i ),
{ Numerical single-wavelength image response function at crystal rotation angle θ i }= R λ ( θ i ),
I mono ( θ i )= I up ( θ i )× R λ ( θ i ),
I mono = i=0 n I mono ( θ i ) .
I λ = i=0 n I up ( θ i )
I hsp =I λ 1 , I λ 2 ... I λ m .

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