OSA's Digital Library

Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Editor: Franco Gori
  • Vol. 30, Iss. 10 — Oct. 1, 2013
  • pp: 1994–2001

Deconvolution-based deblurring of reconstructed images in photoacoustic/thermoacoustic tomography

Nadaparambil Aravindakshan Rejesh, Harish Pullagurla, and Manojit Pramanik  »View Author Affiliations


JOSA A, Vol. 30, Issue 10, pp. 1994-2001 (2013)
http://dx.doi.org/10.1364/JOSAA.30.001994


View Full Text Article

Enhanced HTML    Acrobat PDF (1195 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

Photoacoustic/thermoacoustic tomography is an emerging hybrid imaging modality combining optical/microwave imaging with ultrasound imaging. Here, a k-wave MATLAB toolbox was used to simulate various configurations of excitation pulse shape, width, transducer types, and target object sizes to see their effect on the photoacoustic/thermoacoustic signals. A numerical blood vessel phantom was also used to demonstrate the effect of various excitation pulse waveforms and pulse widths on the reconstructed images. Reconstructed images were blurred due to the broadening of the pressure waves by the excitation pulse width as well as by the limited transducer bandwidth. The blurring increases with increase in pulse width. A deconvolution approach is presented here with Tikhonov regularization to correct the photoacoustic/thermoacoustic signals, which resulted in improved reconstructed images by reducing the blurring effect. It is observed that the reconstructed images remain unaffected by change in pulse widths or pulse shapes, as well as by the limited bandwidth of the ultrasound detectors after the use of the deconvolution technique.

© 2013 Optical Society of America

OCIS Codes
(100.1830) Image processing : Deconvolution
(170.3010) Medical optics and biotechnology : Image reconstruction techniques
(170.5120) Medical optics and biotechnology : Photoacoustic imaging

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: July 10, 2013
Revised Manuscript: August 19, 2013
Manuscript Accepted: August 21, 2013
Published: September 12, 2013

Citation
Nadaparambil Aravindakshan Rejesh, Harish Pullagurla, and Manojit Pramanik, "Deconvolution-based deblurring of reconstructed images in photoacoustic/thermoacoustic tomography," J. Opt. Soc. Am. A 30, 1994-2001 (2013)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-30-10-1994


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. L. H. V. Wang and S. Hu, “Photoacoustic tomography: in vivo imaging from organelles to organs,” Science 335, 1458–1462 (2012). [CrossRef]
  2. V. Ntziachristos, J. Ripoll, L. H. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23, 313–320 (2005). [CrossRef]
  3. D. X. Wang, Y. Pang, G. Ku, X. Xie, G. Stoica, and L. H. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21, 803–806 (2003). [CrossRef]
  4. A. A. Oraevsky, “Optoacoustic imaging of blood for visualization and diagnostics of breast cancer,” Proc. SPIE 4618, 81–94 (2002). [CrossRef]
  5. 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]
  6. D. Razansky, S. Kellnberger, and V. Ntziachristos, “Near-field radiofrequency thermoacoustic tomography with impulse excitation,” Med. Phys. 37, 4602–4607 (2010). [CrossRef]
  7. M. Pramanik, G. Ku, C. H. Li, and L. H. V. Wang, “Design and evaluation of a novel breast cancer detection system combining both thermoacoustic (TA) and photoacoustic (PA) tomography,” Med. Phys. 35, 2218–2223 (2008). [CrossRef]
  8. S. A. Ermilov, T. Khamapirad, A. Conjusteau, M. H. Leonard, R. Lacewell, K. Mehta, T. Miller, and A. A. Oraevsky, “Laser optoacoustic imaging system for detection of breast cancer,” J. Biomed. Opt. 14, 024007 (2009). [CrossRef]
  9. R. A. Kruger, K. D. Miller, H. E. Reynolds, W. L. Kiser, D. R. Reinecke, and G. A. Kruger, “Breast cancer in vivo: contrast enhancement with thermoacoustic CT at 434 MHz-feasibility study,” Radiology 216, 279–283 (2000).
  10. S. Manohar, S. E. Vaartjes, J. C. G. van Hespen, J. M. Klaase, F. M. van den Engh, W. Steenbergen, and T. G. van Leeuwen, “Initial results of in vivo non-invasive cancer imaging in the human breast using near-infrared photoacoustics,” Opt. Express 15, 12277 (2007). [CrossRef]
  11. D. Piras, W. Steenbergen, T. G. van Leeuwen, and S. Manohar, “Photoacoustic imaging of the breast using the twente photoacoustic mammoscope: present status and future perspectives,” IEEE J. Sel. Top. Quantum Electron. 16, 730–739 (2010). [CrossRef]
  12. Y. Xu and L. H. V. Wang, “Rhesus monkey brain imaging through intact skull with thermoacoustic tomography,” IEEE Trans. Ultrason. Ferroelectr. Freq. Control 53, 542–548 (2006). [CrossRef]
  13. C. H. Li and L. H. V. Wang, “Photoacoustic tomography of the mouse cerebral cortex with a high-numerical-aperture-based virtual point detector,” J. Biomed. Opt. 14, 024047 (2009). [CrossRef]
  14. R. I. Siphanto, K. K. Thumma, R. G. M. Kolkman, T. G. van Leeuwen, F. F. M. de Mul, J. W. van Neck, L. N. A. van Adrichem, and W. Steenbergen, “Serial noninvasive photoacoustic imaging of neovascularization in tumor angiogenesis,” Opt. Express 13, 89–95 (2005). [CrossRef]
  15. K. H. Song, E. W. Stein, J. A. Margenthaler, and L. H. V. Wang, “Noninvasive photoacoustic identification of sentinel lymph nodes containing methylene blue in vivo in a rat model,” J. Biomed. Opt. 13, 054033 (2008). [CrossRef]
  16. T. N. Erpelding, C. Kim, M. Pramanik, L. Jankovic, K. Maslov, Z. Guo, J. A. Margenthaler, M. D. Pashley, and L. H. V. Wang, “Sentinel lymph nodes in the rat: noninvasive photoacoustic and U.S. imaging with a clinical U.S. system,” Radiology 256, 102–110 (2010). [CrossRef]
  17. D. Pan, M. Pramanik, A. Senpan, S. Ghosh, S. A. Wickline, L. H. V. Wang, and G. M. Lanza, “Near infrared photoacoustic detection of sentinel lymph nodes with gold nanobeacons,” Biomaterials 31, 4088–4093 (2010). [CrossRef]
  18. M. Pramanik, K. H. Song, M. Swierczewska, D. Green, B. Sitharaman, and L. H. V. Wang, “In vivo carbon nanotube-enhanced non-invasive photoacoustic mapping of the sentinel lymph node,” Phys. Med. Biol. 54, 3291–3301 (2009). [CrossRef]
  19. X. Wang, D. R. Bauer, J. L. Vollin, D. G. Manzi, R. S. Wittie, and H. Xin, “Impact of microwave pulses on thermoacoustic imaging applications,” IEEE Antennas Wireless Propag. Lett. 11, 1634 (2012). [CrossRef]
  20. C. Lou, L. Nie, and D. Xu, “Effect of excitation pulse on thermoacoustic signal characteristics and the corresponding algorithm for optimization of image resolution,” J. Appl. Phys. 110, 083101 (2011). [CrossRef]
  21. B. E. Treeby and B. T. Cox, “k-wave: MATLAB toolbox for the simulation and reconstruction of photoacoustic wave-fields,” J. Biomed. Opt. 15, 021314 (2010). [CrossRef]
  22. R. G. M. Kolkman, W. Steenbergen, and T. G. V. Leeuwen, “In vivo photoacoustic imaging of blood vessels with a pulsed laser diode,” Lasers Med. Sci. 21, 134–139 (2006). [CrossRef]
  23. L. Zeng, G. Liu, D. Yang, and X. Ji, “3D-visual laser-diode-based photoacoustic imaging,” Opt. Express 20, 1237–1246 (2012). [CrossRef]
  24. M. Haltmeier and G. Zangerl, “Spatial resolution in photoacoustic tomography: effects of detector size and detector bandwidth,” Inverse Probl. 26, 125002 (2010). [CrossRef]
  25. M. Xu and L. H. V. Wang, “Analytic explanation of spatial resolution related to bandwidth and detector aperture size in thermoacoustic or photoacoustic reconstruction,” Phys. Rev. E 67, 056605 (2003). [CrossRef]
  26. S. M. Riad, “The deconvolution problem: an overview,” Proc. IEEE 74, 82–85 (1986). [CrossRef]
  27. Y. Wang, D. Xing, Y. G. Zeng, and Q. Chen, “Photoacoustic imaging with deconvolution algorithm,” Phys. Med. Biol. 49, 3117–3124 (2004). [CrossRef]
  28. T. Lu and H. Mao, “Deconvolution algorithm with LTI Wiener filter in photoacousic tomography,” in Photonics and Optoelectronics SOPO, Wuhan, 2009.
  29. Z. Dogan, T. Blu, and D. van de Ville, “Eigensensing and deconvolution for the reconstruction of heat absorption profiles from photoacoustic tomography data,” in Proceedings of the Tenth IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI’13) (IEEE, 2013), pp. 1142–1145.
  30. A. N. Tikhonov and V. Y. Arsenirl, Solution of Ill-Posed Problems (Halsted, 1977).
  31. R. C. Aster, B. Borchers, and C. H. Thurber, Parameter Estimation and Inverse Problems (Elsevier, 2013).
  32. C. B. Shaw, J. Prakash, M. Pramanik, and P. K. Yalavarthy, “LSQR-based decomposition provides an efficient way of computing optimal regularization parameter in photoacoustic tomography,” J. Biomed. Opt. 18, 080501 (2013). [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.


« Previous Article  |  Next Article »

OSA is a member of CrossRef.

CrossCheck Deposited