Abstract

Challenges remain in resolving drug distributions within small animals utilizing fluorescence diffuse optical tomography (FDOT). In this paper, we present a new method for detecting and visualizing organs with different kinetics utilizing principal component analysis (PCA). Indocynaine green (ICG) metabolic processes are simulated and imaged using FDOT. When applied to the time series of generated FDOT images, PCA provides a set of the principal components (PCs) which can represent spatial patterns associated with different kinetic behavior. Simulation and experiment studies are both performed to validate the performance of the proposed algorithm. The results suggest that we are able to extract and illustrate changes in ICG kinetic behavior between the heart and the lungs.

© 2010 OSA

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2009

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

D. Wang, X. Liu, and J. Bai, “Analysis of fast full angle fluorescence diffuse optical tomography with beam-forming illumination,” Opt. Express 17(24), 21376–21395 (2009).
[CrossRef] [PubMed]

D. Wang, X. Liu, Y. Chen, and J. Bai, “A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media,” IEEE Trans. Inf. Technol. Biomed. 13(5), 766–773 (2009).
[CrossRef] [PubMed]

2008

G. Hu, J. Yao, and J. Bai, “Full-angle optical imaging of near-infrared fluorescent probes implanted in small animals,” Prog. Nat. Sci. 18(6), 707–711 (2008).
[CrossRef]

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

2007

2006

V. Saxena, M. Sadoqi, and J. Shao, “Polymeric nanoparticulate delivery system for Indocyanine green: biodistribution in healthy mice,” Int. J. Pharm. 308(1-2), 200–204 (2006).
[CrossRef] [PubMed]

2005

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005).
[CrossRef] [PubMed]

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[CrossRef] [PubMed]

S. V. Patwardhan, S. R. Bloch, S. A. Achilefu, and J. P. Culver, “Time-dependent whole-body fluorescence tomography of probe bio-distributions in mice,” Opt. Express 13(7), 2564–2577 (2005).
[CrossRef] [PubMed]

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

2004

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

A. Joshi, W. Bangerth, and E. M. Sevick-Muraca, “Adaptive finite element based tomography for fluorescence optical imaging in tissue,” Opt. Express 12(22), 5402–5417 (2004).
[CrossRef] [PubMed]

2003

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

R. Weissleder and V. Ntziachristos, “Shedding light onto live molecular targets,” Nat. Med. 9(1), 123–128 (2003).
[CrossRef] [PubMed]

2002

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[CrossRef] [PubMed]

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” Neuroimage 17(3), 1521–1537 (2002).
[CrossRef] [PubMed]

2000

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]

1999

A. H. Andersen, D. M. Gash, and M. J. Avison, “Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework,” Magn. Reson. Imaging 17(6), 795–815 (1999).
[CrossRef] [PubMed]

1995

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

1994

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

1993

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

1989

K. Esbensen and P. Geladi, “Strategy of multivariate image analysis (MIA),” Chemom. Intell. Lab. Syst. 7(1-2), 67–86 (1989).
[CrossRef]

1987

Achilefu, S. A.

Alexandrakis, G.

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005).
[CrossRef] [PubMed]

Andersen, A. H.

A. H. Andersen, D. M. Gash, and M. J. Avison, “Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework,” Magn. Reson. Imaging 17(6), 795–815 (1999).
[CrossRef] [PubMed]

Arridge, S. R.

A. Corlu, R. Choe, T. Durduran, M. A. Rosen, M. Schweiger, S. R. Arridge, M. D. Schnall, and A. G. Yodh, “Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans,” Opt. Express 15(11), 6696–6716 (2007).
[CrossRef] [PubMed]

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

Avison, M. J.

A. H. Andersen, D. M. Gash, and M. J. Avison, “Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework,” Magn. Reson. Imaging 17(6), 795–815 (1999).
[CrossRef] [PubMed]

Bai, J.

D. Wang, X. Liu, and J. Bai, “Analysis of fast full angle fluorescence diffuse optical tomography with beam-forming illumination,” Opt. Express 17(24), 21376–21395 (2009).
[CrossRef] [PubMed]

D. Wang, X. Liu, Y. Chen, and J. Bai, “A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media,” IEEE Trans. Inf. Technol. Biomed. 13(5), 766–773 (2009).
[CrossRef] [PubMed]

G. Hu, J. Yao, and J. Bai, “Full-angle optical imaging of near-infrared fluorescent probes implanted in small animals,” Prog. Nat. Sci. 18(6), 707–711 (2008).
[CrossRef]

X. Song, D. Wang, N. Chen, J. Bai, and H. Wang, “Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm,” Opt. Express 15(26), 18300–18317 (2007).
[CrossRef] [PubMed]

Bangerth, W.

Bengtsson, E.

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

Bentolila, L. A.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Bergström, M.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Bergströme, M.

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

Bloch, S. R.

Blomquist, G.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Bogdanov, A.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

Bremer, C.

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[CrossRef] [PubMed]

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]

Chatziioannou, A.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Chatziioannou, A. F.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005).
[CrossRef] [PubMed]

Chen, N.

Chen, Y.

D. Wang, X. Liu, Y. Chen, and J. Bai, “A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media,” IEEE Trans. Inf. Technol. Biomed. 13(5), 766–773 (2009).
[CrossRef] [PubMed]

Choe, R.

Chow, P.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Corlu, A.

Culver, J. P.

de Kleine, R.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

Deliolanis, N.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

Delpy, D. T.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

Dogdas, B.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

Doose, S.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Durduran, T.

Economou, E. N.

Engler, H.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Esbensen, K.

K. Esbensen and P. Geladi, “Strategy of multivariate image analysis (MIA),” Chemom. Intell. Lab. Syst. 7(1-2), 67–86 (1989).
[CrossRef]

Estrada, S.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Frackowiak, R. S. J.

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

Friston, K. J.

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

Frith, C. D.

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

Gambhir, S.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Gambhir, S. S.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Garofalakis, A.

Gash, D. M.

A. H. Andersen, D. M. Gash, and M. J. Avison, “Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework,” Magn. Reson. Imaging 17(6), 795–815 (1999).
[CrossRef] [PubMed]

Geladi, P.

K. Esbensen and P. Geladi, “Strategy of multivariate image analysis (MIA),” Chemom. Intell. Lab. Syst. 7(1-2), 67–86 (1989).
[CrossRef]

Graves, E.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

Graves, E. E.

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

Grimm, J.

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

Haller, J.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

Harshman, R. A.

C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” Neuroimage 17(3), 1521–1537 (2002).
[CrossRef] [PubMed]

Hillman, E. M. C.

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]

Hiraoka, M.

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

Hu, G.

G. Hu, J. Yao, and J. Bai, “Full-angle optical imaging of near-infrared fluorescent probes implanted in small animals,” Prog. Nat. Sci. 18(6), 707–711 (2008).
[CrossRef]

Hyde, D.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

Josephson, L.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

Joshi, A.

Kawata, S.

Kioussis, D.

Långström, B.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

Leahy, R. M.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Lewis, X.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Li, J. J.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Liddle, P. F.

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

Liu, X.

D. Wang, X. Liu, Y. Chen, and J. Bai, “A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media,” IEEE Trans. Inf. Technol. Biomed. 13(5), 766–773 (2009).
[CrossRef] [PubMed]

D. Wang, X. Liu, and J. Bai, “Analysis of fast full angle fluorescence diffuse optical tomography with beam-forming illumination,” Opt. Express 17(24), 21376–21395 (2009).
[CrossRef] [PubMed]

Mamalaki, C.

Menon, R. S.

C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” Neuroimage 17(3), 1521–1537 (2002).
[CrossRef] [PubMed]

Meyer, H.

Michalet, X.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Minami, S.

Montet, X.

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

Moore, A.

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]

Niedre, M.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

Ntziachristos, V.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

H. Meyer, A. Garofalakis, G. Zacharakis, S. Psycharakis, C. Mamalaki, D. Kioussis, E. N. Economou, V. Ntziachristos, and J. Ripoll, “Noncontact optical imaging in mice with full angular coverage and automatic surface extraction,” Appl. Opt. 46(17), 3617–3627 (2007).
[CrossRef] [PubMed]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[CrossRef] [PubMed]

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

R. Weissleder and V. Ntziachristos, “Shedding light onto live molecular targets,” Nat. Med. 9(1), 123–128 (2003).
[CrossRef] [PubMed]

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[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]

Patwardhan, S. V.

Pedersen, F.

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

Pinaud, F. F.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Psycharakis, S.

Rannou, F. R.

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005).
[CrossRef] [PubMed]

Razifar, P.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Ringheim, A.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

Ripoll, J.

H. Meyer, A. Garofalakis, G. Zacharakis, S. Psycharakis, C. Mamalaki, D. Kioussis, E. N. Economou, V. Ntziachristos, and J. Ripoll, “Noncontact optical imaging in mice with full angular coverage and automatic surface extraction,” Appl. Opt. 46(17), 3617–3627 (2007).
[CrossRef] [PubMed]

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[CrossRef] [PubMed]

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

Rosen, M. A.

Sadoqi, M.

V. Saxena, M. Sadoqi, and J. Shao, “Polymeric nanoparticulate delivery system for Indocyanine green: biodistribution in healthy mice,” Int. J. Pharm. 308(1-2), 200–204 (2006).
[CrossRef] [PubMed]

Sasaki, K.

Saxena, V.

V. Saxena, M. Sadoqi, and J. Shao, “Polymeric nanoparticulate delivery system for Indocyanine green: biodistribution in healthy mice,” Int. J. Pharm. 308(1-2), 200–204 (2006).
[CrossRef] [PubMed]

Schellenberger, E. A.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

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]

Schnall, M. D.

Schweiger, M.

A. Corlu, R. Choe, T. Durduran, M. A. Rosen, M. Schweiger, S. R. Arridge, M. D. Schnall, and A. G. Yodh, “Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans,” Opt. Express 15(11), 6696–6716 (2007).
[CrossRef] [PubMed]

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

Sevick-Muraca, E. M.

Shao, J.

V. Saxena, M. Sadoqi, and J. Shao, “Polymeric nanoparticulate delivery system for Indocyanine green: biodistribution in healthy mice,” Int. J. Pharm. 308(1-2), 200–204 (2006).
[CrossRef] [PubMed]

Silverman, R.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Song, X.

Soubret, A.

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[CrossRef] [PubMed]

Stout, D.

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Sundaresan, G.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Thomas, C. G.

C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” Neuroimage 17(3), 1521–1537 (2002).
[CrossRef] [PubMed]

Tsay, J. M.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Tung, C. H.

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[CrossRef] [PubMed]

Wang, D.

Wang, H.

Wang, L. V.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Weiss, S.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Weissleder, R.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

R. Weissleder and V. Ntziachristos, “Shedding light onto live molecular targets,” Nat. Med. 9(1), 123–128 (2003).
[CrossRef] [PubMed]

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[CrossRef] [PubMed]

Wu, A. M.

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Yao, J.

G. Hu, J. Yao, and J. Bai, “Full-angle optical imaging of near-infrared fluorescent probes implanted in small animals,” Prog. Nat. Sci. 18(6), 707–711 (2008).
[CrossRef]

Yessayan, D.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[CrossRef] [PubMed]

Yodh, A. G.

A. Corlu, R. Choe, T. Durduran, M. A. Rosen, M. Schweiger, S. R. Arridge, M. D. Schnall, and A. G. Yodh, “Three-dimensional in vivo fluorescence diffuse optical tomography of breast cancer in humans,” Opt. Express 15(11), 6696–6716 (2007).
[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]

Zacharakis, G.

Appl. Opt.

Cancer Res.

X. Montet, V. Ntziachristos, J. Grimm, and R. Weissleder, “Tomographic fluorescence mapping of tumor targets,” Cancer Res. 65(14), 6330–6336 (2005).
[CrossRef] [PubMed]

Chemom. Intell. Lab. Syst.

K. Esbensen and P. Geladi, “Strategy of multivariate image analysis (MIA),” Chemom. Intell. Lab. Syst. 7(1-2), 67–86 (1989).
[CrossRef]

Eur. J. Nucl. Med.

F. Pedersen, M. Bergströme, E. Bengtsson, and B. Långström, “Principal component analysis of dynamic positron emission tomography images,” Eur. J. Nucl. Med. 21(12), 1285–1292 (1994).
[CrossRef] [PubMed]

IEEE Trans. Inf. Technol. Biomed.

D. Wang, X. Liu, Y. Chen, and J. Bai, “A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media,” IEEE Trans. Inf. Technol. Biomed. 13(5), 766–773 (2009).
[CrossRef] [PubMed]

IEEE Trans. Med. Imaging

A. Soubret, J. Ripoll, and V. Ntziachristos, “Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio,” IEEE Trans. Med. Imaging 24(10), 1377–1386 (2005).
[CrossRef] [PubMed]

Int. J. Pharm.

V. Saxena, M. Sadoqi, and J. Shao, “Polymeric nanoparticulate delivery system for Indocyanine green: biodistribution in healthy mice,” Int. J. Pharm. 308(1-2), 200–204 (2006).
[CrossRef] [PubMed]

J. Appl. Physiol.

J. Haller, D. Hyde, N. Deliolanis, R. de Kleine, M. Niedre, and V. Ntziachristos, “Visualization of pulmonary inflammation using noninvasive fluorescence molecular imaging,” J. Appl. Physiol. 104(3), 795–802 (2008).
[CrossRef] [PubMed]

J. Cereb. Blood Flow Metab.

K. J. Friston, C. D. Frith, P. F. Liddle, and R. S. J. Frackowiak, “Functional connectivity: the principal-component analysis of large (PET) data sets,” J. Cereb. Blood Flow Metab. 13(1), 5–14 (1993).
[CrossRef] [PubMed]

J. Opt. Soc. Am. A

Magn. Reson. Imaging

A. H. Andersen, D. M. Gash, and M. J. Avison, “Principal component analysis of the dynamic response measured by fMRI: a generalized linear systems framework,” Magn. Reson. Imaging 17(6), 795–815 (1999).
[CrossRef] [PubMed]

Med. Phys.

E. E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. 30(5), 901–911 (2003).
[CrossRef] [PubMed]

M. Schweiger, S. R. Arridge, M. Hiraoka, and D. T. Delpy, “The finite element method for the propagation of light in scattering media: boundary and source conditions,” Med. Phys. 22(11), 1779–1792 (1995).
[CrossRef] [PubMed]

Mol. Imaging Biol.

D. Stout, P. Chow, R. Silverman, R. M. Leahy, X. Lewis, S. Gambhir, and A. Chatziioannou, “Creating a whole body digital mouse atlas with PET, CT and cryosection images,” Mol. Imaging Biol. 4, S27 (2002).

Nat. Biotechnol.

V. Ntziachristos, J. Ripoll, L. V. Wang, and R. Weissleder, “Looking and listening to light: the evolution of whole-body photonic imaging,” Nat. Biotechnol. 23(3), 313–320 (2005).
[CrossRef] [PubMed]

Nat. Med.

V. Ntziachristos, C. H. Tung, C. Bremer, and R. Weissleder, “Fluorescence molecular tomography resolves protease activity in vivo,” Nat. Med. 8(7), 757–761 (2002).
[CrossRef] [PubMed]

R. Weissleder and V. Ntziachristos, “Shedding light onto live molecular targets,” Nat. Med. 9(1), 123–128 (2003).
[CrossRef] [PubMed]

Nat. Photonics

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]

Neuroimage

C. G. Thomas, R. A. Harshman, and R. S. Menon, “Noise reduction in BOLD-based fMRI using component analysis,” Neuroimage 17(3), 1521–1537 (2002).
[CrossRef] [PubMed]

Opt. Express

Phys. Med. Biol.

P. Razifar, H. Engler, G. Blomquist, A. Ringheim, S. Estrada, B. Långström, and M. Bergström, “Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer’s disease,” Phys. Med. Biol. 54(11), 3595–3612 (2009).
[CrossRef] [PubMed]

B. Dogdas, D. Stout, A. F. Chatziioannou, and R. M. Leahy, “Digimouse: a 3D whole body mouse atlas from CT and cryosection data,” Phys. Med. Biol. 52(3), 577–587 (2007).
[CrossRef] [PubMed]

G. Alexandrakis, F. R. Rannou, and A. F. Chatziioannou, “Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study,” Phys. Med. Biol. 50(17), 4225–4241 (2005).
[CrossRef] [PubMed]

Proc. Natl. Acad. Sci. U.S.A.

V. Ntziachristos, E. A. Schellenberger, J. Ripoll, D. Yessayan, E. Graves, A. Bogdanov, L. Josephson, and R. Weissleder, “Visualization of antitumor treatment by means of fluorescence molecular tomography with an annexin V-Cy5.5 conjugate,” Proc. Natl. Acad. Sci. U.S.A. 101(33), 12294–12299 (2004).
[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]

Prog. Nat. Sci.

G. Hu, J. Yao, and J. Bai, “Full-angle optical imaging of near-infrared fluorescent probes implanted in small animals,” Prog. Nat. Sci. 18(6), 707–711 (2008).
[CrossRef]

Science

X. Michalet, F. F. Pinaud, L. A. Bentolila, J. M. Tsay, S. Doose, J. J. Li, G. Sundaresan, A. M. Wu, S. S. Gambhir, and S. Weiss, “Quantum dots for live cells, in vivo imaging, and diagnostics,” Science 307(5709), 538–544 (2005).
[CrossRef] [PubMed]

Other

A. Kak, and M. Slaney, Computerized Tomographic Imaging (New York: IEEE Press, 1987), ch. 7.

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Figures (11)

Fig. 1
Fig. 1

The flowchart of the proposed algorithm.

Fig. 2
Fig. 2

The schematic of the imaging system.

Fig. 3
Fig. 3

Setup for simulation studies. (a) The mouse geometry model used in simulation studies. The gray part in (a) depicts the mouse surface with a length of 1.6 cm from the neck to the base of the lungs. The red part in (a) depicts anatomical information of the heart and the green part in (a) depicts anatomical information of the lungs. In order to reduce the boundary artifacts which interfere with the finite element computation, the model is generated by sampling the original atlas data (intersections of the vertical and horizontal lines) and then approximating the curves using spline function to form the torso surface. (b) ICG concentration time course in the heart and the lungs after tail vein injection. The circles in (b) depict actual concentration value at corresponding time points according to [30]. Different colors correspond to different time course curves (red:heart; green:lungs).

Fig. 4
Fig. 4

Setup for experiment studies. (a) Experiment setup. Two glass tubes (diameter of 0.3 cm and height of 0.6 cm) filled with different concentrations of ICG were placed inside a cylinder phantom (a glass cylinder of 3.0 cm diameter filled with 1% intralipid). The edge to edge distance along Y axis was 0.2 cm. (b) ICG concentration time course in tube 1 and tube 2. Tube 1 simulated ICG metabolic processes in the heart and tube 2 simulated ICG metabolic processes in the lungs. The circles in (b) depicted actual concentration value at corresponding time points. Different colors corresponded to different time course curves (red:tube 1; green:tube 2).

Fig. 5
Fig. 5

Reconstruction of synthetic data from a dynamic study of ICG metabolic processes in the heart and the lungs. The images are at z = 0.8 cm. (a)-(f) The reconstructed results at 5 min, 10 min, 15 min, 30 min, 60 min, and 120 min. Different colors correspond to actual boundary of different organs (red:heart; green:lungs; yellow:surface).

Fig. 6
Fig. 6

The PC images obtained when PCA was applied to D-FDOT images shown in Fig. 5. (a)-(f) The six positive PC images. (g)-(l) The six negative PC images. In the PC2 image, the uptake of ICG in the heart (negative) and the lungs (positive) was indicated. Different colors corresponded to actual boundary of different organs (red:heart; green:lungs; yellow:surface).

Fig. 7
Fig. 7

The 3-D visualization results of the PC2 images. (a) and (d) The 3-D visualization results of the negative and the positive PC2 images obtained when PCA was applied to the D-FDOT images at all slices. (a) indicated the uptake of ICG in the heart. (d) indicated the uptake of ICG in the lungs. (b) and (e) The 3-D anatomical information of the heart and the lungs in the mouse. (c) and (f) A visual comparison of the PC2 images in (a) and (d) to anatomical information in (b) and (e). The red parts in (c) and (f) indicated the 3-D anatomical information of the heart and the lungs. The green parts in (c) and (f) indicated the 3-D visualization results of the negative and the positive PC2 images.

Fig. 8
Fig. 8

Pictogram of how principal component expansion works with D-FDOT images. In this plot, we show how the reconstructed results ( X ¯ 1 , X ¯ 2 , ... , X ¯ 6 ) in Fig. 5 (after subtraction of the mean value) were transformed into six principal components (PC1,PC2, ... ,PC6) that were presented as images through the matrix E. The red part in the PC2 image indicated the uptake of ICG in the heart and the green part in the PC2 image indicated the uptake of ICG in the lungs. The black curves in 3-D view depicted the height of selected dynamic tomographic images. The 3-D view (left) depicted the 3-D reconstructed results of frame 1 (5 min). The 3-D view (right) depicted the merged results of the positive and the negative PC2 images. The red part in 3-D view (right) depicted the 3-D visualization results of the negative PC2 images in Fig. 7(a). The green part in 3-D view (right) depicted the 3-D visualization results of the positive PC2 images in Fig. 7(d).

Fig. 9
Fig. 9

Reconstruction of experimental data at different frames. The images are at z = 3.0 cm. (a)-(f) Reconstruction results at frames 1 to 6. The red curve on the cross images depicts the phantom boundary, and the black circles depict the actual tubes. All images are displayed at the same range.

Fig. 10
Fig. 10

Comparison of reconstructed result to PCA-based result. (a) The 2-D reconstructed result of frame 3. The cross section image is at z = 3.0 cm, which is depicted by the red curve in (d). The red circle in (a) depicts the phantom boundary, and the black circles depict the actual tubes. (b) and (c) The positive and the negative PC3 images obtained when PCA was applied to D-FDOT images shown in Fig. 9. The red circles in (b) and (c) depict the phantom boundary, and the cyan circles in (b) and (c) depict the actual tubes. (d) The 3-D reconstructed result of frame 3. (e) and (f) The 3-D visualization results of the positive and the negative PC3 images obtained when PCA was applied to the D-FDOT images at all slices.

Fig. 11
Fig. 11

The merged results of the positive and the negative PC3 images. (a) The 2-D merged results of the positive PC3 image in Fig. 10(b) and the negative PC3 image in Fig. 10(c). The cross section image is at z = 3.0 cm, which is depicted by the red curves in (b) and (c). The red circle in (a) depicts the phantom boundary, and the cyan circles depict the actual tubes. (b) and (c) The 3-D merged results of the positive PC3 images in Fig. 10(e) and the negative PC3 images in Fig. 10(f) using different views. The red parts indicate the uptake of ICG in tube 1 that is used to simulate ICG metabolic processes in the heart. The green parts indicate the uptake of ICG in tube 2 that is used to simulate ICG metabolic processes in the lungs.

Tables (1)

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Table 1 Optical parameters of biological tissues in mouse at 700-800 nm a

Equations (7)

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{ [ D ( r ) G ( r s , r ) ] μ a ( r ) G ( r s , r ) = δ ( r r s ) r Ω 2 q D ( r ) G ( r s , r ) n + G ( r s , r ) = 0 r Ω ,
Φ m ( r d ) Φ x ( r d ) = Θ V G ( r d , r p ) G ( r s , r p ) n ( r p ) G ( r s , r d ) d r p ,
Φ m ( r d 1 ) Φ x ( r d 1 ) = Θ Δ V G ( r s 1 , r d 1 ) [ G ( r d 1 , r 1 ) G ( r 1 , r s 1 ) , ... , G ( r d N , r N ) G ( r N , r s N ) ] [ n ( r 1 ) . . . n ( r N ) ] ,
[ Φ m ( r d 1 ) / Φ x ( r d 1 ) . . . Φ m ( r d M ) / Φ x ( r d M ) ] = [ W 11 . . . W 1 N . . . . . . . . . W M 1 . . . W M N ] [ n ( r 1 ) . . . n ( r N ) ] .
S = 1 M 1 X ¯ T X ¯ ,
P = X ¯ E ,
P i = t N e t , i X ¯ t .

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