OSA's Digital Library

Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 4 — Feb. 14, 2011
  • pp: 3175–3184

Blind source unmixing in multi-spectral optoacoustic tomography

Jürgen Glatz, Nikolaos C. Deliolanis, Andreas Buehler, Daniel Razansky, and Vasilis Ntziachristos  »View Author Affiliations

Optics Express, Vol. 19, Issue 4, pp. 3175-3184 (2011)

View Full Text Article

Enhanced HTML    Acrobat PDF (1032 KB)

Browse Journals / Lookup Meetings

Browse by Journal and Year


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools



Multispectral optoacoustic (photoacoustic) tomography (MSOT) is a hybrid modality that can image through several millimeters to centimeters of diffuse tissues, attaining resolutions typical of ultrasound imaging. The method can further identify tissue biomarkers by decomposing the spectral contributions of different photo-absorbing molecules of interest. In this work we investigate the performance of blind source unmixing methods and spectral fitting approaches in decomposing the contributions of fluorescent dyes from the tissue background, based on MSOT measurements in mice. We find blind unmixing as a promising method for accurate MSOT decomposition, suitable also for spectral unmixing in fluorescence imaging. We further demonstrate its capacity with temporal unmixing on real-time MSOT data obtained in-vivo for enhancing the visualization of absorber agent flow in the mouse vascular system.

© 2011 Optical Society of America

OCIS Codes
(170.5120) Medical optics and biotechnology : Photoacoustic imaging
(170.6280) Medical optics and biotechnology : Spectroscopy, fluorescence and luminescence
(170.6960) Medical optics and biotechnology : Tomography
(100.1455) Image processing : Blind deconvolution

ToC Category:
Medical Optics and Biotechnology

Original Manuscript: November 2, 2010
Revised Manuscript: January 25, 2011
Manuscript Accepted: January 30, 2011
Published: February 3, 2011

Virtual Issues
Vol. 6, Iss. 3 Virtual Journal for Biomedical Optics

Jürgen Glatz, Nikolaos C. Deliolanis, Andreas Buehler, Daniel Razansky, and Vasilis Ntziachristos, "Blind source unmixing in multi-spectral optoacoustic tomography," Opt. Express 19, 3175-3184 (2011)

Sort:  Author  |  Year  |  Journal  |  Reset  


  1. H. Zhang, K. Maslov, G. Stoica, and L. Wang, “Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging,” Nat. Biotechnol. 24, 848–851 (2006). [CrossRef] [PubMed]
  2. M. Xu, and L. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77, 041101 (2006). [CrossRef]
  3. V. Ntziachristos, “Going deeper than microscopy: the optical imaging frontier in biology,” Nat. Methods 7, 603–614 (2010). [CrossRef] [PubMed]
  4. C. G. A. Hoelen, F. F. M. de Mul, R. Pongers, and A. Dekker, “Three-dimensional photoacoustic imaging of blood vessels in tissue,” Opt. Lett. 23, 648–650 (1998). [CrossRef]
  5. H. Fang, K. Maslov, and L. V. Wang, “Photoacoustic doppler effect from flowing small light-absorbing particles,” Phys. Rev. Lett. 99, 184501 (2007). [CrossRef] [PubMed]
  6. P.-C. Li, S.-W. Huang, C.-W. Wei, Y.-C. Chiou, C.-D. Chen, and C.-R. C. Wang, “Photoacoustic flow measurements by use of laser-induced shape transitions of gold nanorods,” Opt. Lett. 30, 3341–3343 (2005). [CrossRef]
  7. V. Ntziachristos, and D. Razansky, “Molecular imaging by means of multispectral optoacoustic tomography (MSOT),” Chem. Rev. 110, 2783–2794 (2010). [CrossRef] [PubMed]
  8. H.-P. Brecht, R. Su, M. Fronheiser, S. A. Ermilov, A. Conjusteau, and A. A. Oraevsky, “Whole-body threedimensional optoacoustic tomography system for small animals,” J. Biomed. Opt. 14, 064007 (2009). [CrossRef]
  9. J. Gamelin, A. Maurudis, A. Aguirre, F. Huang, P. Guo, L. V. Wang, and Q. Zhu, “A real-time photoacoustic tomography system for small animals,” Opt. Express 17, 10489–10498 (2009). [CrossRef] [PubMed]
  10. A. Buehler, E. Herzog, D. Razansky, and V. Ntziachristos, “Video rate optoacoustic tomography of mouse kidney perfusion,” Opt. Lett. 35, 2475–2477 (2010). [CrossRef] [PubMed]
  11. G. Busse, and A. Rosencwaig, “Subsurface imaging with photoacoustics,” Appl. Phys. Lett. 36, 815–816 (1980). [CrossRef]
  12. A. Rosencwaig, “Potential clinical applications of photoacoustics,” Clin. Chem. 28, 1878–1881 (1982). [PubMed]
  13. X. Wang, X. Xie, G. Ku, L. V. Wang, and G. Stoica, “Noninvasive imaging of hemoglobin concentration and oxygenation in the rat brain using high-resolution photoacoustic tomography,” J. Biomed. Opt. 11, 024015 (2006). [CrossRef] [PubMed]
  14. D. Razansky, C. Vinegoni, and V. Ntziachristos, “Multispectral photoacoustic imaging of fluorochromes in small animals,” Opt. Lett. 32, 2891–2893 (2007). [CrossRef] [PubMed]
  15. D. Razansky, M. Distel, C. Vinegoni, R. Ma, M. Perrimon, R. W. Koster, and V. Ntziachristos, “Multispectral opto-acoustic tomography of deep-seated fluorescent proteins in vivo,” Nat. Photonics 3, 412–417 (2009). [CrossRef]
  16. P.-C. Li, C.-R. C. Wang, D.-B. Shieh, C.-W. Wei, C.-K. Liao, C. Poe, S. Jhan, A.-A. Ding, and Y.-N. Wu, “In vivo photoacoustic molecular imaging withsimultaneous multiple selective targeting using antibody-conjugated gold nanorods,” Opt. Express 16, 18605–18615 (2008). [CrossRef]
  17. A. Taruttis, E. Herzog, D. Razansky, and V. Ntziachristos, “Real-time imaging of cardiovascular dynamics and circulating gold nanorods with multispectral optoacoustic tomography,” Opt. Express 18, 19592–19602 (2010). [CrossRef] [PubMed]
  18. D. Razansky, J. Baeten, and V. Ntziachristos, “Sensitivity of molecular target detection by multispectral optoacoustic tomography (MSOT),” Med. Phys. 36, 939–945 (2009). [CrossRef] [PubMed]
  19. A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28, 1997–2006 (2009). [CrossRef] [PubMed]
  20. I. T. Jolliffe, Principal Component Analysis, 2nd ed. (Springer, 2002).
  21. A. Cichocki, R. Zdunek, A. H. Phan, and S. I. Amari, Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation, 1st ed. (Wiley, 2009). [PubMed]
  22. R. Tauler, B. Kowalski, and S. Fleming, “Multivariate curve resolution applied to spectral data from multiple runs of an industrial process,” Anal. Chem. 65, 2040–2047 (1993). [CrossRef]
  23. A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis, Adaptive and Learning Systems for Signal Processing, Communications, and Control, 1st ed. (Wiley InterScience, 2002).
  24. M. Funaro, E. Oja, and H. Valpola, “Independent component analysis for artefact separation in astrophysical images,” Neural Netw. 16, 469–478 (2003). [CrossRef] [PubMed]
  25. B. A. Draper, K. Baek, M. S. Bartlett, and J. R. Beveridge, “Recognizing faces with pca and ica,” Comput. Vis. Image Underst. 91, 115–137 (2003). [CrossRef]
  26. J. Yang, D. Zhang, A. F. Frangi, and J. Y. Yang, “Two-dimensional pca: a new approach to appearance-based face representation and recognition,” IEEE Trans. Pattern Anal. Mach. Intell. 26, 131–137 (2004). [CrossRef] [PubMed]
  27. E. M. C. Hillman, and A. Moore, “All optical anatomical co registration for molecular imaging of small animals using dynamic contrast,” Nat. Photonics 1(9), 526–530 (2007). [CrossRef]
  28. H. Xu, and B. W. Rice, “In-vivo fluorescence imaging with a multivariate curve resolution spectral unmixing technique,” J. Biomed. Opt. 14, 064011 (2009). [CrossRef]
  29. A.-S. Montcuquet, L. Herv’e, F. Navarro, J.-M. Dinten, and J. I. Mars, “Nonnegative matrix factorization: a blind spectra separation method for in vivo fluorescent optical imaging,” J. Biomed. Opt. 15, 056009 (2010). [CrossRef] [PubMed]
  30. S. Clémençon, and S. Slim, “On portfolio selection under extreme risk measure: the heavy-tailed ICA Model,” Int. J. Theor. Appl. Finance 10, 449–474 (2007). [CrossRef]
  31. N. Keshava, “A survey of spectral unmixing algorithms,” Lincoln Lab. J. 14, 55–78 (2003).
  32. E. Moore, “On the reciprocal of the general algebraic matrix,” Bull. Am. Math. Soc. 26, 394–395 (1920).
  33. R. Penrose, “A generalized inverse for matrices,” in Proceedings of the Cambridge Philosophical Society (1955) Vol. 51, pp. 406–412. [CrossRef]
  34. K. Pearson, “On lines and planes of closest fit to a system of points in space,” London, Edinburgh Dublin Philos, Mag. J. Sci. 6, 559–572 (1901).
  35. S. M. Kay, Fundamentals of Statistical Signal Processing, 1st ed. (Prentice Hall PTR, 1993),Vol. 1.
  36. J. Nash, “The singular-value decomposition and its use to solve least-squares problems,” in Compact Numerical Methods for Computers: Linear Algebra and Function Minimization, 2nd ed. (Inst. of Physics Pub., 1990), pp. 30–48.
  37. L. Le Cam, “The central limit theorem around 1935,” Stat. Sci. 1, 78–91 (1986). [CrossRef]
  38. A. Hyvrinen, “Fast and robust fixed-point algorithms for independent component analysis,” IEEE Trans. Neural Netw. 10, 626–634 (1999). [CrossRef]
  39. M. Xu, and L. V. Wang, “Universal back-projection algorithm for photoacoustic computed tomography,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71, 016706 (2005). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


Fig. 1 Fig. 2 Fig. 3
Fig. 4 Fig. 5

« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited