Abstract

Photoacoustic imaging is a hybrid imaging modality capable of producing contrast similar to optical imaging techniques but with increased penetration depth and resolution in turbid media by encoding the information as acoustic waves. In general, it is important to characterize the performance of a photoacoustic imaging system by parameters such as sensitivity, resolution, and contrast. However, system characterization can extend beyond these metrics by implementing advanced analysis via the crosstalk matrix and singular value decomposition. A method was developed to experimentally measure a matrix that represented the imaging operator for a photoacoustic imaging system. Computations to produce the crosstalk matrix were completed to provide insight into the spatially dependent sensitivity and aliasing for the photoacoustic imaging system. Further analysis of the imaging operator was done via singular value decomposition to estimate the capability of the imaging system to reconstruct objects and the inherent sensitivity to those objects. The results provided by singular value decomposition were compared to SVD results from a de-noised imaging operator to estimate the number of measurable singular vectors for the system. These characterization techniques can be broadly applied to any photoacoustic system and, with regards to the studied system, could be used as a basis for improvements to future iterations.

© 2010 OSA

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    [CrossRef]
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    [CrossRef]
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2009 (1)

2008 (2)

P. Ephrat, M. Roumeliotis, F. S. Prato, and J. J. Carson, “Four-dimensional photoacoustic imaging of moving targets,” Opt. Express 16(26), 21570–21581 (2008).
[CrossRef] [PubMed]

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

2006 (1)

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[CrossRef]

2004 (1)

J. Qi and R. H. Huesman, “Wavelet crosstalk matrix and its application to assessment of shift-variant imaging systems,” IEEE Trans. Nucl. Sci. 51(1), 123–129 (2004).
[CrossRef]

2002 (1)

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

2001 (1)

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

2000 (1)

1998 (2)

1995 (1)

1991 (1)

G. J. Diebold, T. Sun, and M. I. Khan, “Photoacoustic monopole radiation in one, two, and three dimensions,” Phys. Rev. Lett. 67(24), 3384–3387 (1991).
[CrossRef] [PubMed]

Barrett, H. H.

Carson, J. J.

Carson, J. J. L.

M. Roumeliotis, P. Ephrat, J. Patrick, and J. J. L. Carson, “Development and characterization of an omnidirectional photoacoustic point source for calibration of a staring 3D photoacoustic imaging system,” Opt. Express 17(17), 15228–15238 (2009).
[CrossRef] [PubMed]

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

de Mul, F. F.

Denny, J. L.

Diebold, G. J.

G. J. Diebold, T. Sun, and M. I. Khan, “Photoacoustic monopole radiation in one, two, and three dimensions,” Phys. Rev. Lett. 67(24), 3384–3387 (1991).
[CrossRef] [PubMed]

Ephrat, P.

Frauchiger, D.

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Frenz, M.

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Hoelen, C. G. A.

Huesman, R. H.

J. Qi and R. H. Huesman, “Wavelet crosstalk matrix and its application to assessment of shift-variant imaging systems,” IEEE Trans. Nucl. Sci. 51(1), 123–129 (2004).
[CrossRef]

Jacques, S. L.

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

Keenliside, L.

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

Khan, M. I.

G. J. Diebold, T. Sun, and M. I. Khan, “Photoacoustic monopole radiation in one, two, and three dimensions,” Phys. Rev. Lett. 67(24), 3384–3387 (1991).
[CrossRef] [PubMed]

Kostli, K. P.

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Liu, P.

P. Liu, “The P-transform and photoacoustic image reconstruction,” Phys. Med. Biol. 43(3), 667–674 (1998).
[CrossRef] [PubMed]

Myers, K. J.

Niederhauser, J. J.

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Paltauf, G.

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Patrick, J.

Prahl, S. A.

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

Prato, F. S.

P. Ephrat, M. Roumeliotis, F. S. Prato, and J. J. Carson, “Four-dimensional photoacoustic imaging of moving targets,” Opt. Express 16(26), 21570–21581 (2008).
[CrossRef] [PubMed]

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

Qi, J.

J. Qi and R. H. Huesman, “Wavelet crosstalk matrix and its application to assessment of shift-variant imaging systems,” IEEE Trans. Nucl. Sci. 51(1), 123–129 (2004).
[CrossRef]

Roumeliotis, M.

Seabrook, A.

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

Sun, T.

G. J. Diebold, T. Sun, and M. I. Khan, “Photoacoustic monopole radiation in one, two, and three dimensions,” Phys. Rev. Lett. 67(24), 3384–3387 (1991).
[CrossRef] [PubMed]

Viator, J. A.

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

Wagner, R. F.

Wang, L. V.

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[CrossRef]

Weber, H. P.

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

Wilson, D. W.

Xu, M.

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[CrossRef]

Appl. Opt. (1)

IEEE J. Sel. Top. Quantum Electron. (1)

K. P. Kostli, D. Frauchiger, J. J. Niederhauser, G. Paltauf, H. P. Weber, and M. Frenz, “Optoacoustic imaging using a three-dimensional reconstruction algorithm,” IEEE J. Sel. Top. Quantum Electron. 7(6), 918–923 (2001).
[CrossRef]

IEEE Trans. Nucl. Sci. (1)

J. Qi and R. H. Huesman, “Wavelet crosstalk matrix and its application to assessment of shift-variant imaging systems,” IEEE Trans. Nucl. Sci. 51(1), 123–129 (2004).
[CrossRef]

J. Acoust. Soc. Am. (1)

G. Paltauf, J. A. Viator, S. A. Prahl, and S. L. Jacques, “Iterative reconstruction algorithm for optoacoustic imaging,” J. Acoust. Soc. Am. 112(4), 1536–1544 (2002).
[CrossRef] [PubMed]

J. Biomed. Opt. (1)

P. Ephrat, L. Keenliside, A. Seabrook, F. S. Prato, and J. J. L. Carson, “Three-dimensional photoacoustic imaging by sparse-array detection and iterative image reconstruction,” J. Biomed. Opt. 13(5), 054052 (2008).
[CrossRef] [PubMed]

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

Opt. Express (3)

Phys. Med. Biol. (1)

P. Liu, “The P-transform and photoacoustic image reconstruction,” Phys. Med. Biol. 43(3), 667–674 (1998).
[CrossRef] [PubMed]

Phys. Rev. Lett. (1)

G. J. Diebold, T. Sun, and M. I. Khan, “Photoacoustic monopole radiation in one, two, and three dimensions,” Phys. Rev. Lett. 67(24), 3384–3387 (1991).
[CrossRef] [PubMed]

Rev. Sci. Instrum. (1)

M. Xu and L. V. Wang, “Photoacoustic imaging in biomedicine,” Rev. Sci. Instrum. 77(4), 041101 (2006).
[CrossRef]

Other (7)

T. Lu, J. Jiang, Y. Su, R. K. Wang, F. Zhang, and J. Yao, Photoacoustic imaging: Its current status and future development” in 4th International Conference on Photonics and Imaging in Biology and Medicine, September 03,2005- September 06 (SPIE), National Natural Science Foundation of China; SPIE Russia Chapter; Int. Laser Center of M.V. Lomoson Moscow State Univ.; Bio-optics and Laser Medicine Comm. of Chinese Optics Soc.; Science and Techn. Garden of Tianjin University, China.

A. A. Oraevsky, V. G. Andreev, A. A. Karabutov, and R. O. Esenaliev, Two-dimensional opto-acoustic tomography transducer array and image reconstruction algorithm,” Proc SPIE Int Soc Opt Eng 3601, 256–267 (1999).

D. Frauchiger, K. P. Kostli, G. Paltauf, M. Frenz, and H. P. Weber, Optoacoustic tomography using a two dimensional optical pressure transducer and two different reconstruction algorithms” in Hybrid and Novel Imaging and New Optical Instrumentation for Biomedical Applications, June18,2001- June 21 (SPIE), 74–80.

M. Xu, and L. V. Wang, “RF-induced thermoacoustic tomography” in Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS), October23,2002- October 26 (Institute of Electrical and Electronics Engineers Inc), 1211–1212.

D. Modgil, M. A. Anastasio, and P. J. La Riviere, Photoacoustic image reconstruction in an attenuating medium using singular value decomposition” in Photons Plus Ultrasound: Imaging and Sensing2009 (SPIE - The International Society for Optical Engineering), 71771B (7 pp.).

P. Ephrat, and J. J. L. Carson, Measurement of photoacoustic detector sensitivity distribution by robotic source placement” in 9th Conference on Photons Plus Ultrasound: Imaging and Sensing 2008, January20,2008- January 23 (SPIE), Society of Photo-Optical Instrumentation Engineers (SPIE).

H. H. Barrett, and H. Gifford, Cone-beam tomography with discrete data sets” in Second International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 451–76.

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Figures (5)

Fig. 1.
Fig. 1.

(a) Isometric view of the hemispherical PA imaging array illustrating the transducer arrangement, placement of the liquid reservoir, and the optical fiber PA source. (b) Example of raw data acquired on a single acoustic transducer.

Fig. 2.
Fig. 2.

Displays sensitivity of the PA system at each location in object space acquired from the main-diagonal of the crosstalk matrix corresponding to the 30×30×30 mm3. Both x and y axes represent voxel number in the y and z directions, respectively. Accordingly, each x-plane in object space is 10×10 voxels.

Fig. 3.
Fig. 3.

(a) Illustrates aliasing from the center voxel for the 16×16×16 mm3 scan (each x-plane is 8×8 voxels) while (b) shows aliasing from the same position for the 30×30×30 mm3 scan (each x-plane is 10×10 voxels). (c) Shows representative aliasing plots from a voxel located at the corner of the imaging volume for the 30×30×30 mm3 scan (each x-plane is 10×10 voxels).

Fig. 4.
Fig. 4.

(a) and (b) Displays the center y-z plane of the first 8 singular vectors acquired via experiment and de-noised, respectively. The field-of-view for each singular vector is 30×30 mm2. The singular vector number reads from left to right with the leftmost image representing singular vector 1.

Fig. 5.
Fig. 5.

(a) Displays the correlation among the set of 1000 corresponding singular vectors in the de-noised and experimental matrices, (V)T. (b) Shows the same computation as in (a) but in descending order for an imaging operator with (i) ½ the intrinsic system noise, (ii) ¼ the intrinsic system noise, (iii) the experimental imaging operator, (iv) 2 times the intrinsic system noise, and (v) 5 times the intrinsic noise. The singular vector index changed with the order as the true singular vector number (corresponding to the matrix (V)T) was unknown after the initial projection operations were completed. The vertical axis in both (a) and (b) is shared.

Equations (4)

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g = Hf
H = US V T
B = H T H
B jj = k = 1 K ( H jk T H j k )

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