Abstract

Photoacoustic tomography (PAT) is a hybrid imaging modality that takes advantage of high optical contrast brought by optical imaging and high spatial resolution brought by ultrasound imaging. However, the quantification in photoacoustic imaging is challenging. Multiple optical illumination approach has proven to achieve uncoupling of diffusion and absorption effects. In this paper, this protocol is adopted and synthetic photoacoustic data, blurred with some noise, were generated. The influence of the distribution of optical sources and transducers on the reconstruction of the absorption and diffusion coefficients maps is studied. Specific situations with limited view angles were examined. The results show multiple illuminations with a wide field improve the reconstructions.

© 2014 Optical Society of America

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2014 (1)

Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
[Crossref] [PubMed]

2013 (1)

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

2012 (6)

2011 (3)

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

G. Bal and K. Ren, “Multiple-source quantitative photoacoustic tomography,” Inverse Probl. 27, 075003 (2011).
[Crossref]

P. Shao, B. Cox, and R. J. Zemp, “Estimating optical absorption, scattering, and Grueneisen distributions with multiple-illumination photoacoustic tomography,” Appl. Opt. 50(19), 3145–3154 (2011).
[Crossref] [PubMed]

2010 (1)

G. Bal and G. Uhlmann, “Inverse diffusion theory of photoacoustics,” Inverse Probl. 26, 085010 (2010).

2009 (4)

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28(12), 1997–2006 (2009).
[Crossref] [PubMed]

J. R. Rajian, P. L. Carson, and X. Wang, “Quantitative photoacoustic measurement of tissue optical absorption spectrum aided by an optical contrast agent,” Opt. Express 17(6), 4879–4889 (2009).
[Crossref] [PubMed]

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(2), 024007 (2009).
[Crossref] [PubMed]

C. Li and L. V. Wang, “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol. 54(19), R59–R97 (2009).
[Crossref] [PubMed]

2008 (1)

2007 (3)

H. F. Zhang, K. Maslov, and L. V. Wang, “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc. 2(4), 797–804 (2007).
[Crossref] [PubMed]

D. Razansky, C. Vinegoni, and V. Ntziachristos, “Multispectral photoacoustic imaging of fluorochromes in small animals,” Opt. Lett. 32(19), 2891–2893 (2007).
[Crossref] [PubMed]

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

2006 (1)

2005 (1)

J. Ripoll and V. Ntziachristos, “Quantitative point source photoacoustic inversion formulas for scattering and absorbing media,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(3), 031912 (2005).
[Crossref] [PubMed]

2003 (1)

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

2000 (1)

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
[Crossref] [PubMed]

Arridge, S.

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

Arridge, S. R.

T. Tarvainen, B. T. Cox, J. P. Kaipio, and S. R. Arridge, “Reconstructing absorption and scattering distributions in quantitative photoacoustic tomography,” Inverse Probl. 28(8), 084009 (2012).
[Crossref]

B. T. Cox, S. R. Arridge, K. P. Köstli, and P. C. Beard, “Two-dimensional quantitative photoacoustic image reconstruction of absorption distributions in scattering media by use of a simple iterative method,” Appl. Opt. 45(8), 1866–1875 (2006).
[Crossref] [PubMed]

Bagchi, S.

Bal, G.

G. Bal and K. Ren, “On multi-spectral quantitative photoacoustic tomography in diffusive regime,” Inverse Probl. 28(2), 025010 (2012).
[Crossref]

G. Bal and K. Ren, “Multiple-source quantitative photoacoustic tomography,” Inverse Probl. 27, 075003 (2011).
[Crossref]

G. Bal and G. Uhlmann, “Inverse diffusion theory of photoacoustics,” Inverse Probl. 26, 085010 (2010).

Banerjee, B.

Bauer, A. Q.

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

Beard, P. C.

Carson, P. L.

Chance, B.

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
[Crossref] [PubMed]

Conjusteau, A.

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(2), 024007 (2009).
[Crossref] [PubMed]

Cox, B.

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

P. Shao, B. Cox, and R. J. Zemp, “Estimating optical absorption, scattering, and Grueneisen distributions with multiple-illumination photoacoustic tomography,” Appl. Opt. 50(19), 3145–3154 (2011).
[Crossref] [PubMed]

Cox, B. T.

T. Tarvainen, B. T. Cox, J. P. Kaipio, and S. R. Arridge, “Reconstructing absorption and scattering distributions in quantitative photoacoustic tomography,” Inverse Probl. 28(8), 084009 (2012).
[Crossref]

B. T. Cox, S. R. Arridge, K. P. Köstli, and P. C. Beard, “Two-dimensional quantitative photoacoustic image reconstruction of absorption distributions in scattering media by use of a simple iterative method,” Appl. Opt. 45(8), 1866–1875 (2006).
[Crossref] [PubMed]

Culver, J. P.

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

Daoudi, K.

Ermilov, S. A.

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(2), 024007 (2009).
[Crossref] [PubMed]

Erpelding, T. N.

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

Harrison, T.

Heijblom, M.

Hondebrink, E.

Hussain, A.

Kaipio, J. P.

T. Tarvainen, B. T. Cox, J. P. Kaipio, and S. R. Arridge, “Reconstructing absorption and scattering distributions in quantitative photoacoustic tomography,” Inverse Probl. 28(8), 084009 (2012).
[Crossref]

Khamapirad, T.

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(2), 024007 (2009).
[Crossref] [PubMed]

Klaase, J. M.

Köstli, K. P.

Kottmann, J.

Ku, G.

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Lacewell, R.

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(2), 024007 (2009).
[Crossref] [PubMed]

Leonard, M. H.

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(2), 024007 (2009).
[Crossref] [PubMed]

Li, C.

C. Li and L. V. Wang, “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol. 54(19), R59–R97 (2009).
[Crossref] [PubMed]

Luginbühl, J.

Manohar, S.

Maslov, K.

H. F. Zhang, K. Maslov, and L. V. Wang, “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc. 2(4), 797–804 (2007).
[Crossref] [PubMed]

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

Maslov, K. I.

Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
[Crossref] [PubMed]

Mehta, K.

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(2), 024007 (2009).
[Crossref] [PubMed]

Miller, T.

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(2), 024007 (2009).
[Crossref] [PubMed]

Nothdurft, R. E.

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

Ntziachristos, V.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28(12), 1997–2006 (2009).
[Crossref] [PubMed]

D. Razansky, C. Vinegoni, and V. Ntziachristos, “Multispectral photoacoustic imaging of fluorochromes in small animals,” Opt. Lett. 32(19), 2891–2893 (2007).
[Crossref] [PubMed]

J. Ripoll and V. Ntziachristos, “Quantitative point source photoacoustic inversion formulas for scattering and absorbing media,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(3), 031912 (2005).
[Crossref] [PubMed]

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
[Crossref] [PubMed]

Oraevsky, A. A.

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(2), 024007 (2009).
[Crossref] [PubMed]

Pang, Y. J.

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Piras, D.

Rajian, J. R.

Razansky, D.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28(12), 1997–2006 (2009).
[Crossref] [PubMed]

D. Razansky, C. Vinegoni, and V. Ntziachristos, “Multispectral photoacoustic imaging of fluorochromes in small animals,” Opt. Lett. 32(19), 2891–2893 (2007).
[Crossref] [PubMed]

Reichmann, E.

Ren, K.

G. Bal and K. Ren, “On multi-spectral quantitative photoacoustic tomography in diffusive regime,” Inverse Probl. 28(2), 025010 (2012).
[Crossref]

G. Bal and K. Ren, “Multiple-source quantitative photoacoustic tomography,” Inverse Probl. 27, 075003 (2011).
[Crossref]

Rey, J. M.

Ripoll, J.

J. Ripoll and V. Ntziachristos, “Quantitative point source photoacoustic inversion formulas for scattering and absorbing media,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(3), 031912 (2005).
[Crossref] [PubMed]

Rosenthal, A.

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28(12), 1997–2006 (2009).
[Crossref] [PubMed]

Roy, D.

Saratoon, T.

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

Schnall, M.

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
[Crossref] [PubMed]

Shao, P.

Sigrist, M. W.

Sivaramakrishnan, M.

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

Steenbergen, W.

Stoica, G.

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Tarvainen, T.

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

T. Tarvainen, B. T. Cox, J. P. Kaipio, and S. R. Arridge, “Reconstructing absorption and scattering distributions in quantitative photoacoustic tomography,” Inverse Probl. 28(8), 084009 (2012).
[Crossref]

Uhlmann, G.

G. Bal and G. Uhlmann, “Inverse diffusion theory of photoacoustics,” Inverse Probl. 26, 085010 (2010).

van den Engh, F. M.

van Hespen, J. C. G.

van Leeuwen, T. G.

Vasu, R. M.

Vinegoni, C.

Wang, L. V.

Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
[Crossref] [PubMed]

A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
[Crossref] [PubMed]

C. Li and L. V. Wang, “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol. 54(19), R59–R97 (2009).
[Crossref] [PubMed]

H. F. Zhang, K. Maslov, and L. V. Wang, “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc. 2(4), 797–804 (2007).
[Crossref] [PubMed]

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Wang, X.

Wang, X. D.

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Xia, W.

Xie, X. Y.

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
[Crossref] [PubMed]

Yao, J.

Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
[Crossref] [PubMed]

Yodh, A. G.

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
[Crossref] [PubMed]

Zemp, R. J.

Zhang, H. F.

H. F. Zhang, K. Maslov, and L. V. Wang, “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc. 2(4), 797–804 (2007).
[Crossref] [PubMed]

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

Zhou, Y.

Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
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Appl. Opt. (2)

Appl. Phys. Lett. (1)

H. F. Zhang, K. Maslov, M. Sivaramakrishnan, G. Stoica, and L. V. Wang, “Imaging of hemoglobin oxygen saturation variations in single vessels in vivo using photoacoustic microscopy,” Appl. Phys. Lett. 90, 053901 (2007).

Biomed. Opt. Express (2)

IEEE Trans. Med. Imaging (1)

A. Rosenthal, D. Razansky, and V. Ntziachristos, “Quantitative optoacoustic signal extraction using sparse signal representation,” IEEE Trans. Med. Imaging 28(12), 1997–2006 (2009).
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Inverse Probl. (5)

G. Bal and K. Ren, “On multi-spectral quantitative photoacoustic tomography in diffusive regime,” Inverse Probl. 28(2), 025010 (2012).
[Crossref]

G. Bal and G. Uhlmann, “Inverse diffusion theory of photoacoustics,” Inverse Probl. 26, 085010 (2010).

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G. Bal and K. Ren, “Multiple-source quantitative photoacoustic tomography,” Inverse Probl. 27, 075003 (2011).
[Crossref]

T. Saratoon, T. Tarvainen, B. Cox, and S. Arridge, “A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation,” Inverse Probl. 29(7), 075006 (2013).
[Crossref]

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A. Q. Bauer, R. E. Nothdurft, T. N. Erpelding, L. V. Wang, and J. P. Culver, “Quantitative photoacoustic imaging: correcting for heterogeneous light fluence distributions using diffuse optical tomography,” J. Biomed. Opt. 16(9), 096016 (2011).
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Y. Zhou, J. Yao, K. I. Maslov, and L. V. Wang, “Calibration-free absolute quantification of particle concentration by statistical analyses of photoacoustic signals in vivo,” J. Biomed. Opt. 19(3), 037001 (2014).
[Crossref] [PubMed]

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(2), 024007 (2009).
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J. Opt. Soc. Am. A (1)

Nat. Biotechnol. (1)

X. D. Wang, Y. J. Pang, G. Ku, X. Y. Xie, G. Stoica, and L. V. Wang, “Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain,” Nat. Biotechnol. 21(7), 803–806 (2003).
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Nat. Protoc. (1)

H. F. Zhang, K. Maslov, and L. V. Wang, “In vivo imaging of subcutaneous structures using functional photoacoustic microscopy,” Nat. Protoc. 2(4), 797–804 (2007).
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Opt. Express (3)

Opt. Lett. (1)

Phys. Med. Biol. (1)

C. Li and L. V. Wang, “Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol. 54(19), R59–R97 (2009).
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Phys. Rev. E Stat. Nonlin. Soft Matter Phys. (1)

J. Ripoll and V. Ntziachristos, “Quantitative point source photoacoustic inversion formulas for scattering and absorbing media,” Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 71(3), 031912 (2005).
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Proc. Natl. Acad. Sci. U.S.A. (1)

V. Ntziachristos, A. G. Yodh, M. Schnall, and B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. U.S.A. 97(6), 2767–2772 (2000).
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H. Gao, H. Zhao, and S. Osher, “Bregman methods in quantitative photoacoustic tomography,” Univ. Calif. Los Angel. UCLA Comput. Appl. Math. Rep. Vol. 10 – 42, (2010).

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Figures (6)

Fig. 1
Fig. 1 Left: Geometry of the simulated object, light sources and transducers are placed respectively 0.3 cm and 2 cm away from the object. In the reconstruction area are placed the perturbations: two absorbers ( δ μ a , positions: (0.6cm;1cm) and (1.6cm;1cm), dimensions: 0.3cm × 1.1cm and 0.3cm × 0.3cm) and one diffuser ( δD , position: (1cm;1cm), dimensions: 0.5cm × 0.5cm). Right: Different meshes used in the simulations: left, FEM mesh { r Δ } ; middle, reconstruction square mesh { r j } ; right: modelling square mesh { r l } .
Fig. 2
Fig. 2 Comparison of different reconstruction methods at different noise levels: Left, results of the reconstructions of the perturbations on the absorption δ μ a and diffusion δD coefficient maps; Right: cross-plots of the values extracted from a horizontal line in the middle of the vertical axis in the reconstruction areas.
Fig. 3
Fig. 3 Influence of the number of sources. Left Top: reconstructed perturbation absorption δ μ a and diffusion δD coefficient maps with (a) 2, (b) 4, (c) 8 and (d) 16 point sources illuminations. Left Bottom: Quadratic errors on the reconstructions of the absorption (black circles) and diffusion (blue squares) coefficients perturbations as a function of the number of point sources. Right Top: Normalized singular values (Left) and condition number of (H) as a function of the number of sources (Right). Right Bottom: cross-plots of the values extracted from a horizontal line in the middle of the vertical axis in the reconstruction areas.
Fig. 4
Fig. 4 Influence of the detectors distributions. Left Top: reconstructed perturbation absorption δ μ a and diffusion δD coefficient maps. (a) the detectors are evenly distributed around the object (15 detectors on each side); (b) on each side, the detectors cover a length that is half the length of the object; (c) the length covered by the detectors is half of (b); (d) 30 detectors evenly distributed on each of the two vertical sides of the object; (e) 30 detectors evenly distributed on each of the two horizontal sides of the object. Left Bottom: Quadratic errors on the reconstructions of the absorption (black circles) and diffusion (blue squares) coefficients perturbations for the five different configurations. Right Top: Normalized singular values (Left) and condition number of (H) as a function of the number of sources (Right). Right Bottom: cross-plots of the values extracted from a horizontal line in the middle of the vertical axis in the reconstruction areas.
Fig. 5
Fig. 5 Influence of the sources shape. Left Top: reconstructed perturbation absorption δ μ a and diffusion δD coefficient maps with (a) 4 points sources; 4 line sources with a length of (b) 0.2 mm; (c) 4 mm; (d) 8 mm; (e) 26 mm; (f) full field of view probing with one single source composed of lines. Left Bottom: Quadratic errors on the reconstructions of the absorption (black circles) and diffusion (blue squares) coefficients perturbations as a function of the length of the four sources (“Integral” represents situation (f), reconstructions obtained with a single measurement but with full field of view source illumination). Right Top: Normalized singular values (Left) and condition number of (H) as a function of the number of sources (Right). Right Bottom: cross-plots of the values extracted from a horizontal line in the middle of the vertical axis in the reconstruction areas.
Fig. 6
Fig. 6 Top Left: Schemas of the experimental situations. For each situation, only 4 measurements were performed at 0°, 90°, 180° and 270°, the rotation angles corresponding to rotations around the axis located at point O (cross marker), and perpendicular to the object plan. Schemas correspond to the measurement taken at 0°: (a) 4 points sources, 15 detectors; (b) 4 line sources with length 26 mm, 15 detectors; (c) same line sources, 1 detector; (d) same line sources, 2 detectors; (e) same line sources, 3 detectors; for each situations, four synthetic measurements were considered: these configurations (0°), and object rotated by 90°, 180° and 270°. The condition numbers of the corresponding (H) are reported for each situation. Top Right: reconstructed perturbation absorption δ μ a and diffusion δD coefficient maps. Bottom: Quadratic errors (QE) on the reconstructions of the absorption (black circles) and diffusion (blue squares) coefficients perturbations for the five different configurations.

Equations (9)

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H(r,t)= μ a (r)ϕ(r,t) μ a (r)ϕ(r)δ(t)=E(r)δ(t).
μ a (r)ϕ(r).(D(r)ϕ(r))=Q(r)
( 2 t 2 v s 2 2 )p(r,u,t)= p 0 (r,u) t (δ(t))
p model (r,u,t)= v s 2 0 t d t ' p(r,u, t ' )= d r ' p 0 ( r ' ,u) 4π| r r ' | δ(t | r r ' | v s )
( J T J )δu= J T ΔHδu=b
p s model ( r d ,u, t τ )= l=1 L Γ 4π R dl δ( t τ R dl v s ) E l s Δ V l
J dτ s ( u 0 ( r j ))= p s model ( r d ,u, t τ ) / u | u= u 0 = l=1 L α dl,τ β l,s ( u 0 ( r j ))
β l,s ( u 0 ( r j ))= [ E l s / μ a ( r j ) E l s / D( r j ) ] u= u 0 =[ ϕ s ( r l , u 0 ) δ lj + μ a0 ( r l ) ϕ s ( r l ,u) μ a ( r j ) | u= u 0 μ a0 ( r l ) ϕ s ( r l ,u) D( r j ) | u= u 0 ]
{ ϕ s ( r l ,u) μ a ( r j ) | u= u 0 = G 0 (| r l r j |, u 0 ( r j ))ϕ(| r j r s |, u 0 ( r j ))Δ V j / D 0 ϕ s ( r l ,u) D( r j ) | u= u 0 = G 0 (| r l r j |, u 0 ( r j ))ϕ(| r j r s |, u 0 ( r j ))Δ V j / D 0

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