Abstract

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue.

© 2015 Optical Society of America

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References

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  • Publication
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    [Crossref]
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  10. L. Guolan and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19(1), 010901 (2014).
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    [PubMed]
  14. S. Jacques, “Optical Properties of Aorta,” http://omlc.org/spectra/aorta/ .
  15. M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
    [Crossref]
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  20. J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
    [Crossref]
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    [Crossref] [PubMed]
  23. J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.
  24. W. Kühnel, “Atlas Color de Citología e Histología” (Médica Panamericana, 2005).

2014 (1)

L. Guolan and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19(1), 010901 (2014).
[Crossref]

2013 (2)

R. Jolivot, Y. Benezeth, and F. Marzani, “Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology,” Int. J. Biomed. Imaging. 2013, 978289 (2013).
[PubMed]

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

2012 (1)

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

2011 (2)

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

R. Jolivot, P. Vabres, and F. Marzani, “Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system,” Comput. Med. Imag. Graph. 35(2), 85–88 (2011).
[Crossref]

2010 (1)

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

2009 (1)

2007 (2)

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

C. J. Lin, “Projected gradient methods for nonnegative matrix factorization,” Neural Comput. 19(10), 2756–2779. (2007).
[Crossref] [PubMed]

2005 (1)

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

2000 (2)

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

H. Aapo and E. Oja, “Independent component analysis: algorithms and applications,” Neural Netw.  13(4), 411–430 (2000).
[Crossref]

1999 (1)

D. Lee and H. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature 401(6755), 788–791 (1999).
[Crossref] [PubMed]

a.Jo, J.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Aapo, H.

H. Aapo and E. Oja, “Independent component analysis: algorithms and applications,” Neural Netw.  13(4), 411–430 (2000).
[Crossref]

H. Aapo, J. Karhunen, and E. Oja, Independent Component Analysis (Wiley, 2004).

Aksnes, A.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Anderson, R.

R. Anderson, J. Hu, and J. Parrish, “Optical radiation transfer in the human skin and applications in in vivo remittance spectroscopy,” in Bioengineering and the skin, R. Marks and P. A. Payne, eds. (Springer, 1981).
[Crossref]

Applegate, B. E.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Au, S.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Benezeth, Y.

R. Jolivot, Y. Benezeth, and F. Marzani, “Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology,” Int. J. Biomed. Imaging. 2013, 978289 (2013).
[PubMed]

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Bogers, A.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Brettel, H.

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

Bustamante, J.

S. Perez, J. Garzón, and J. Bustamante, “Acquisition and processing multispectral imaging system to cardiovascular tissue,” in Proceedings of Pan American Health Care Exchanges (PAHCE) (IEEE, 2013), pp. 1–3.

Cardeno, M.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Clubb, F.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Crettez, J.

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

Dimou, A.

Duncker, D.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Eivind, L.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Emile, J.F.

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Fei, B.

L. Guolan and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19(1), 010901 (2014).
[Crossref]

Follen, M.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Fragouli, D. H.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Galeano, J.

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Garzón, J.

S. Perez, J. Garzón, and J. Bustamante, “Acquisition and processing multispectral imaging system to cardiovascular tissue,” in Proceedings of Pan American Health Care Exchanges (PAHCE) (IEEE, 2013), pp. 1–3.

Guolan, L.

L. Guolan and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19(1), 010901 (2014).
[Crossref]

Hardeberg, J.

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

Haugen, O.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Hu, J.

R. Anderson, J. Hu, and J. Parrish, “Optical radiation transfer in the human skin and applications in in vivo remittance spectroscopy,” in Bioengineering and the skin, R. Marks and P. A. Payne, eds. (Springer, 1981).
[Crossref]

Itoh, M.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Jacques, S.

S. Jacques, “Optical Properties of Aorta,” http://omlc.org/spectra/aorta/ .

Jolivot, R.

R. Jolivot, Y. Benezeth, and F. Marzani, “Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology,” Int. J. Biomed. Imaging. 2013, 978289 (2013).
[PubMed]

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

R. Jolivot, P. Vabres, and F. Marzani, “Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system,” Comput. Med. Imag. Graph. 35(2), 85–88 (2011).
[Crossref]

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Karhunen, J.

H. Aapo, J. Karhunen, and E. Oja, Independent Component Analysis (Wiley, 2004).

Koumantakis, E. E.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Kühnel, W.

W. Kühnel, “Atlas Color de Citología e Histología” (Médica Panamericana, 2005).

Lamarque, D.

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Lee, D.

D. Lee and H. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature 401(6755), 788–791 (1999).
[Crossref] [PubMed]

Lin, C. J.

C. J. Lin, “Projected gradient methods for nonnegative matrix factorization,” Neural Comput. 19(10), 2756–2779. (2007).
[Crossref] [PubMed]

MacAulay, C.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Mackinnon, N.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Maitre, H.

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

Marzani, F.

R. Jolivot, Y. Benezeth, and F. Marzani, “Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology,” Int. J. Biomed. Imaging. 2013, 978289 (2013).
[PubMed]

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

R. Jolivot, P. Vabres, and F. Marzani, “Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system,” Comput. Med. Imag. Graph. 35(2), 85–88 (2011).
[Crossref]

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

Mastik, F.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Masuda, Y.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Mitra, J.

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

Nakappan, S.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Oja, E.

H. Aapo and E. Oja, “Independent component analysis: algorithms and applications,” Neural Netw.  13(4), 411–430 (2000).
[Crossref]

H. Aapo, J. Karhunen, and E. Oja, Independent Component Analysis (Wiley, 2004).

Olstad, E.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Orfanoudaki, I. M.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Panayiotides, J. G.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Pande, P.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Park, J.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Park, S. Y.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Parrish, J.

R. Anderson, J. Hu, and J. Parrish, “Optical radiation transfer in the human skin and applications in in vivo remittance spectroscopy,” in Bioengineering and the skin, R. Marks and P. A. Payne, eds. (Springer, 1981).
[Crossref]

Perez, S.

S. Perez, J. Garzón, and J. Bustamante, “Acquisition and processing multispectral imaging system to cardiovascular tissue,” in Proceedings of Pan American Health Care Exchanges (PAHCE) (IEEE, 2013), pp. 1–3.

Pikkula, B. M.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Price, R.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Randeberg, L.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Schmitt, F.

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

Serachitopol, D.

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Seung, H.

D. Lee and H. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature 401(6755), 788–791 (1999).
[Crossref] [PubMed]

Shimada, M.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Shrestha, S.

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Sifakis, S. K.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Svaasand, L.

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

Takahashi, M.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Themelis, G. C.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Umbaugh, S. E.

S. E. Umbaugh, Digital Image Processing and Analysis: Human and Computer Vision applications with CVIPtools (CRC press, 2010).

Vabres, P.

R. Jolivot, P. Vabres, and F. Marzani, “Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system,” Comput. Med. Imag. Graph. 35(2), 85–88 (2011).
[Crossref]

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

Van der Steen, A.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Vazgiouraki, E. M.

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

Wieringa, F.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Yamada, Y.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Yatagai, T.

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Zeelenberg, C.

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

Zonios, G.

Atherosclerosis (1)

J. Park, P. Pande, S. Shrestha, F. Clubb, B. E. Applegate, and J. a.Jo, “Biochemical characterization of atherosclerotic plaques by endogenous multispectral fluorescence lifetime imaging microscopy,” Atherosclerosis 220(2), 394–401 (2012).
[Crossref]

Biomed. Signal. Process. Control. (1)

J. Galeano, R. Jolivot, F. Marzani, and Y. Benezeth, “Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm.,” Biomed. Signal. Process. Control. 8(2), 169–175 (2013).
[Crossref]

Comput. Med. Imag. Graph. (1)

R. Jolivot, P. Vabres, and F. Marzani, “Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system,” Comput. Med. Imag. Graph. 35(2), 85–88 (2011).
[Crossref]

Gynecol. Oncol. (2)

I. M. Orfanoudaki, G. C. Themelis, S. K. Sifakis, D. H. Fragouli, J. G. Panayiotides, E. M. Vazgiouraki, and E. E. Koumantakis, “A clinical study of optical biopsy of the uterine cervix using a multispectral imaging system,” Gynecol. Oncol. 96(1), 119–131 (2005).
[Crossref]

S. Nakappan, S. Y. Park, D. Serachitopol, R. Price, M. Cardeno, S. Au, N. Mackinnon, C. MacAulay, M. Follen, and B. M. Pikkula, “Methodology of a real-time quality control for the multispectral digital colposcope (MDC),” Gynecol. Oncol. 107(1), 215–222 (2007).
[Crossref]

Int. J. Biomed. Imaging. (1)

R. Jolivot, Y. Benezeth, and F. Marzani, “Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology,” Int. J. Biomed. Imaging. 2013, 978289 (2013).
[PubMed]

J. Biomed. Opt. (2)

L. Eivind, L. Randeberg, E. Olstad, O. Haugen, A. Aksnes, and L. Svaasand, “Hyperspectral imaging of atherosclerotic plaques in vitro,” J. Biomed. Opt. 16(2), 026011 (2011).
[Crossref]

L. Guolan and B. Fei, “Medical hyperspectral imaging: a review,” J. Biomed. Opt. 19(1), 010901 (2014).
[Crossref]

Nature (1)

D. Lee and H. Seung, “Learning the parts of objects by non-negative matrix factorization,” Nature 401(6755), 788–791 (1999).
[Crossref] [PubMed]

Neural Comput. (1)

C. J. Lin, “Projected gradient methods for nonnegative matrix factorization,” Neural Comput. 19(10), 2756–2779. (2007).
[Crossref] [PubMed]

Neural Netw (1)

H. Aapo and E. Oja, “Independent component analysis: algorithms and applications,” Neural Netw.  13(4), 411–430 (2000).
[Crossref]

Opt. Express (1)

Opt. Rev. (1)

M. Shimada, Y. Masuda, Y. Yamada, M. Itoh, M. Takahashi, and T. Yatagai, “Explanation of human skin color by multiple linear regression analysis based on the modified Lambert-Beer law,” Opt. Rev. 7(4), 348–352 (2000).
[Crossref]

Proc. SPIE (1)

J. Mitra, R. Jolivot, P. Vabres, and F. Marzani, “Source separation on hyperspectral cube applied to dermatology,” Proc. SPIE 7624, 76243I (2010).
[Crossref]

Other (10)

R. Anderson, J. Hu, and J. Parrish, “Optical radiation transfer in the human skin and applications in in vivo remittance spectroscopy,” in Bioengineering and the skin, R. Marks and P. A. Payne, eds. (Springer, 1981).
[Crossref]

H. Aapo, J. Karhunen, and E. Oja, Independent Component Analysis (Wiley, 2004).

S. Jacques, “Optical Properties of Aorta,” http://omlc.org/spectra/aorta/ .

S. E. Umbaugh, Digital Image Processing and Analysis: Human and Computer Vision applications with CVIPtools (CRC press, 2010).

J. Hardeberg, F. Schmitt, H. Brettel, J. Crettez, and H. Maitre, “Multiespectral Image Acquisition and Simulation of Illuminant Changes,” in Colour Imaging: Vision and Technology, L. MacDonaldNew and M. R. Luo, eds. (Wiley, 1999).

F. Wieringa, F. Mastik, D. Duncker, A. Bogers, C. Zeelenberg, and A. Van der Steen, “Remote Optical Stereoscopic Multispectral Imaging during Cardiac Surgery,” in Proceedings of Computers in Cardiology (IEEE, 2006), pp. 693–696.

World Health Organization, “Cardiovascular diseases (CVDs)” (Fact sheet N. 317. Updated March 2013). http://www.who.int/mediacentre/factsheets/fs317/es/ .

S. Perez, J. Garzón, and J. Bustamante, “Acquisition and processing multispectral imaging system to cardiovascular tissue,” in Proceedings of Pan American Health Care Exchanges (PAHCE) (IEEE, 2013), pp. 1–3.

J. Galeano, R. Jolivot, Y. Benezeth, F. Marzani, J.F. Emile, and D. Lamarque, “Analysis of multispectral images of excised colon tissue samples based on genetic algorithms,” in Proceedings of Eighth International Conference on Signal Image Technology and Internet Based Systems (IEEE, 2012), pp. 833–838.

W. Kühnel, “Atlas Color de Citología e Histología” (Médica Panamericana, 2005).

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Figures (6)
Fig. 1
Fig. 1 Configuration of a system based on interference filters: a). white light source, b). bandpass interference filters, c).liquid guide-light, d). 10X microscope objective, e).CCD camera, and f). sample.

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Fig. 2
Fig. 2 Theoretical absorbance spectra of the major chromophores present in cardiovascular tissue [9, 14].

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Fig. 3
Fig. 3 (a) Image at 600nm from bovine aorta tissue obtained by interference filter-based system. The tissue was illuminated from the lumen side. (b) Sampled spectrum of the ROI denoted by arrows A and B in Fig. (a).

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Fig. 4
Fig. 4 Normalized concentration maps obtained by applying NMF method on cardiovascular tissue multispectral images acquired by the interference filter-based system.

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Fig. 5
Fig. 5 Normalized concentration maps obtained by applying ICA method on cardiovascular tissue multispectral images acquired by the interference filter-based system.

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Fig. 6
Fig. 6 Elastic fibers of aorta media layer: a. Theoretical aorta cross-section [24], b.ICA result.

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Tables (1)

Tables Icon

Table 1 Degree of correlation between: the calculated component’s absorbance and the theoretical one.

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Equations (12)

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I r e f = I r a w − I d a r k I w h i t e − I d a r k
A ( λ ) = α 1 ε H b O 2 ( λ ) + α 2 ε H b ( λ ) + α 3 ε β − c a r ( λ ) + α 4 ε O t h e r s ( λ )
A ( λ ) = − 10 log ( R ( λ ) )
X = M Y X = M W H = B H
M = D ˜ 1 / 2 E ˜ T
h i = b i T X = A T X
K u r t ( y ) = E { y 4 } − 3 ( E { y 2 } ) 2
J ( a ) = E { ( A T X ) 4 } − 3 ( E { ( A T X ) 2 } ) 2
A ← X ( A T X ) 3 − 3 A ( ( A T X ) 3 ) A ← A / ‖ A ‖
a p + 1 = a p + 1 − ∑ j = 1 p a p + 1 T a j a j a p + 1 = a p + 1 / a p + 1 T a p + 1
f ( W , H ) ≡ 1 2 ‖ Y − W H ‖ F 2
W n r ← W n r ( Y H T ) n r ( W H H T ) n r H r m ← W r m ( W T Y ) r m − H r m ( W T W H ) r m

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