## Image-guided diffuse optical fluorescence tomography implemented with Laplacian-type regularization

Optics Express, Vol. 15, Issue 7, pp. 4066-4082 (2007)

http://dx.doi.org/10.1364/OE.15.004066

Acrobat PDF (1563 KB)

### Abstract

A promising method to incorporate tissue structural information into the reconstruction of diffusion-based fluorescence imaging is introduced. The method regularizes the inversion problem with a Laplacian-type matrix, which inherently smoothes pre-defined tissue, but allows discontinuities between adjacent regions. The technique is most appropriately used when fluorescence tomography is combined with structural imaging systems. Phantom and simulation studies were used to illustrate significant improvements in quantitative imaging and linearity of response with the new algorithm. Images of an inclusion containing the fluorophore Lutetium Texaphyrin (Lutex) embedded in a cylindrical phantom are more accurate than in situations where no structural information is available, and edge artifacts which are normally prevalent were almost entirely suppressed. Most importantly, spatial priors provided a higher degree of sensitivity and accuracy to fluorophore concentration, though both techniques suffer from image bias caused by excitation signal leakage. The use of spatial priors becomes essential for accurate recovery of fluorophore distributions in complex tissue volumes. Simulation studies revealed an inability of the “no-priors” imaging algorithm to recover Lutex fluorescence yield in domains derived from T1 weighted images of a human breast. The same domains were reconstructed accurately to within 75% of the true values using prior knowledge of the internal tissue structure. This algorithmic approach will be implemented in an MR-coupled fluorescence spectroscopic tomography system, using the MR images for the structural template and the fluorescence data for region quantification.

© 2007 Optical Society of America

## 1. Introduction

1. D. Y. Paithankar, A. U. Chen, B. W. Pogue, M. S. Patterson, and E. M. Sevick-Muraca, “Imaging of fluorescent yeild and lifetime from multiply scattered light reemitted from random media,” Appl. Opt. **36**,2260–2272 (1997). [CrossRef] [PubMed]

6. V. Ntziachristos and R. Weissleder, “Experimental three-dimensional fluorescence reconstruction of diffuse media by use of a normalized Born approximation,” Opt. Lett. **26**,893–895 (2001). [CrossRef]

10. R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissue with noncontact measurements,” IEEE Trans. Med. Imaging **23**,492–500 (2004). [CrossRef] [PubMed]

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

9. A. Godavarty, A. B. Thompson, R. Roy, M. Gurfinkel, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, “Diagnostic imaging of breast cancer using fluorescence-enhanced optical tomography: phantom studies,” J. Biomed. Opt. **9**,488–496 (2004). [CrossRef] [PubMed]

12. A. Godavarty, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, “Detection of single and multiple targets in tissue phantoms with fluorescence-enhanced optical imaging: feasibility study,” Radiol. **235**,148–154 (2005). [CrossRef]

13. B. Brooksby, S. Jiang, C. Kogel, M. Doyley, H. Dehghani, J. B. Weaver, S. P. Poplack, B. W. Pogue, and K. D. Paulsen, “Magnetic resonance-guided near-infrared tomography of the breast,” Rev. Sci. Instrum. **75**,5262–5270 (2004). [CrossRef]

17. G. Kostenich, A. Orenstein, L. Roitman, Z. Malik, and B. Ehrenberg, “In vivo photodynamic therapy with the new near-IR absorbing water soluble photosensitizer lutetium texaphyrin and a high intensity pulsed light delivery system,” Photochem. & Photobiol. **39**,36–42 (1997). [CrossRef]

## 2. Theory

_{x}) of the fluorescing agent, is modeled by two diffusion equations, where the solution of the first equation provides the driving source term of the second [5

5. A. B. Milstein, O. Seungseok, K. J. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomograhy,” Appl. Opt. **42**,3081–3094 (2003). [CrossRef] [PubMed]

*x*and

*m*represent the excitation and emission fluence at wavelengths λ

_{x}and λ

_{m}, respectively. The intrinsic optical parameters

*μ*and

_{ax,m}*q*

_{0}(

*r*,

*ω*) is an isotropic source and Φ

_{x,m}(

*r*,

*ω*) is the photon fluence rate at position

*r*. The diffusion coefficient is given by

*c(r)*is the speed of light in the medium at any point, defined by

*c*, where

_{o}/n(r)*n(r)*is the index of refraction at the same location and

*c*is the speed of light in vacuum. The fluorescence parameters are the lifetime

_{o}*τ*(

*r*) and the fluorescence yield

*ημ*(

_{af}*r*), the latter a product of the fluorophore’s quantum efficiency

*η*and its absorption coefficient

*μ*(

_{af}*r*).

*ξ*is a point on the external boundary, and

*A*depends upon the relative refractive index (RI) mismatch between tissue Ω and air.

*A*can be derived from Fresnel’s law:

*θ*= arcsin(

_{C}*n*/

_{AIR}*n*

_{1}), the angle at which total internal reflection occurs for photons moving from region Ω with RI

*n*

_{1}to air with RI

*n*

_{AIR}, and

*n*= 1.

_{AIR}### 2.1 Finite element implementation:

21. H. Dehghani, B. Brooksby, K. Vishwanath, B. W. Pogue, and P. K. D., “The effects of internal refractive index variation in near infrared optical tomography: A finite element modeling approach,” Phys. Med. Biol. **48**,2713–2727 (2003). [CrossRef] [PubMed]

_{x,m}(

**r**) is approximated by the piecewise continuous polynomial function

^{h}is a finite dimensional subspace spanned by basis functions {

*u*(

_{i}*r*);

*i*= 1⋯

*V*} chosen to have limited support. The problem of solving for Φ

^{h}

_{x,m}becomes one of sparse matrix inversion, and in this work, a bi-conjugate gradient stabilized solver is used. As developed previously [22

22. S. R. Arridge, M. Schweiger, M. Hiraoka, and D. T. Delpy, “A finite element approach for modeling photon transport in tissue,” Med. Phys. **20**,299–309 (1993). [CrossRef] [PubMed]

23. K. D. Paulsen and H. Jiang, “Spatially varying optical property reconstruction using a finite element diffusion equation approximation,” Med. Phys. **22**,691–701 (1995). [CrossRef] [PubMed]

_{x,m}have entries given by:

_{0}has terms

_{m}for fluorescence re-emission is expressed as

### 2.2 The inverse model

#### 2.2.1 No spatial priors

^{Meas}

_{x,m}, at the tissue surface and calculated data, Φ

^{C}

_{x,m}, from the model Eqs. (1) and (2) by adjusting the spatial distribution of the unknown parameters through minimization of the ‘objective’ function. The objective function for recovering the optical properties at the excitation wavelength,

*μ*= (

_{x}*μ*,

_{ax}*κ*), is given as

_{x}*NM*is the total number of measurements given by the imaging system,

*NN*is the number of parameters representing the optical property distribution which corresponds to the number of nodes in the reconstruction mesh, and

*I*is an

*NN*×

*NN*identity matrix. In general,

*χ*

^{2}will not equal zero, but the values of

*μ*for which

_{x}*μ*. Following the Taylor series method for deriving Newton’s method,

_{x}*μ*based on an expansion around some nearby point

_{x}*μ*, where the second and higher order terms are ignored, leading to the iterative update equation:

_{x0}24. S. R. Arridge and M. Schweiger, “Photon-measurement density functions. Part2: Finite-element-method calculations,” Appl. Opt. **34**,8026–8037 (1995). [CrossRef] [PubMed]

*I*is an identity matrix, and in this work λ is some fixed fraction multiplied by the maximum value on the diagonal of the Hessian matrix

*J*, and is therefore updated at each iteration. To recover the optical properties at the emission wavelength,

^{T}J*μ*= (

_{m}*μ*,

_{am}*κ*), the externally applied illuminating source is changed to one at the emission wavelength and the formulation presented in Eq. (13) is used.

_{m}*ημ*(

_{af}*r*), and the Jacobian can be calculated by similar Adjoint properties described above and in Ref. [5

5. A. B. Milstein, O. Seungseok, K. J. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomograhy,” Appl. Opt. **42**,3081–3094 (2003). [CrossRef] [PubMed]

#### 2.2.2 Spatial priors

*NN*is the number of unknowns in the model [16, 25

25. A. Borsic, W. R. B. Lionheart, and C. N. McLeod, “Generation of anisotropic-smoothness regularization filters for EIT,” IEEE Trans. Med. Imaging **21**,579–587 (2002). [CrossRef] [PubMed]

*β*, balances the effect of the parameters with the model-data mismatch in the same manner as λ in Eq. (13). The dimensionless ‘filter’ matrix,

*L*, is generated using MRI-derived priors and its construction is flexible. In this application, each node in the FEM mesh is labeled according to the region, or tissue type, with which it is associated (in the MR image). The L-matrix represents a Laplacian-type structure, the diagonal of which is

*L*=1 where

_{i,i}*i*is the nodal index. When nodes

*i*and

*j*are in the same region containing

*n*nodes,

*L*=-1/n, otherwise

_{i,j}*L*=0. This effectively relaxes the smoothness constraints at the interface between different tissues, in directions normal to their common boundary. The effect on image quality is similar to that achieved through total variation minimization schemes [27

_{i,j}27. K. D. Paulsen and H. Jiang, “Enhanced frequency-domain optical image reconstruction in tissues through total-variation minimization,” Appl. Opt. **35**,3447–3458 (1996). [CrossRef] [PubMed]

*β*is a fixed fraction multiplied by the maximum value on the diagonal of

*J*. This update formulation is also used to recover the optical properties at the emission wavelength as well as the fluorescence yield, as described in Section 2.2.1.

^{T}J#### 2.2.3 Reconstruction basis

28. K. D. Paulsen, P. Meaney, M. Moskowitz, and J. Sullican Jr., “A dual mesh for finite element based reconstruction algorithms,” IEEE Trans. Med. Imaging **14**,504–514 (1995). [CrossRef] [PubMed]

29. M. Schweiger and S. R. Arridge, “Optical tomographic reconstruction in a complex head model using a priori boundary information,” Phys. Med. Biol. **44**,2703–2722 (1999). [CrossRef] [PubMed]

23. K. D. Paulsen and H. Jiang, “Spatially varying optical property reconstruction using a finite element diffusion equation approximation,” Med. Phys. **22**,691–701 (1995). [CrossRef] [PubMed]

## 3. Methods

### 3.1 Simulation studies

30. B. Brooksby, B. W. Pogue, S. Jiang, H. Dehghani, S. Srinivasan, C. Kogel, T. D. Tosteson, J. Weaver, S. P. Poplack, and K. D. Paulsen, “Imaging breast adipose and fibroglandular tissue molecular signatures using hybrid MRI-guided near-infrared spectral tomography,” Proc. Natl. Acad. Sci. USA **103**,8828–8833 (2006). [CrossRef] [PubMed]

31. S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction,” Acad. Radiol. **13**,195–202 (2006). [CrossRef] [PubMed]

17. G. Kostenich, A. Orenstein, L. Roitman, Z. Malik, and B. Ehrenberg, “In vivo photodynamic therapy with the new near-IR absorbing water soluble photosensitizer lutetium texaphyrin and a high intensity pulsed light delivery system,” Photochem. & Photobiol. **39**,36–42 (1997). [CrossRef]

*ω*= 0.

- Reconstruct for optical properties at the excitation wavelength, μ
_{ax}and μ_{sx}’, with frequency domain data, - Reconstruct for optical properties at the emission wavelength, μ
_{am}and μ_{sm}’, with frequency domain data collected using a laser source at the emission wavelength, - Use the reconstructed optical properties and fluorescence intensity data to recover fluorescence yield.

32. T. O. McBride, B. W. Pogue, S. Jiang, U. L. Osterberg, K. D. Paulsen, and S. P. Poplack, “Initial studies of in vivo absorbing and scattering heterogeneity in near-infrared tomographic breast imaging,” Opt. Lett. **26**,822–824 (2001). [CrossRef]

33. B. W. Pogue, T. O. McBride, J. Prewitt, U. L. Osterberg, and K. D. Paulsen, “Spatially variant regularization improves diffuse optical tomography,” Appl. Opt. **38**,2950–2961 (1999). [CrossRef]

### 3.2 Phantom studies

34. S. Jiang, B. W. Pogue, T. O. McBride, and K. D. Paulsen, “Quantitative analysis of near-infrared tomography: sensitivity to the tissue-simulating precalibration phantom,” J. Biomed. Opt. **8**,308–315 (2003). [CrossRef] [PubMed]

35. B. Pogue and M. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. **11**,0411021–04110216 (2006). [CrossRef]

_{ax}= 0.005 and μ

_{sx}’ = 1.0 mm

^{-1}, measured with a frequency domain system near the excitation wavelength. Unlike the simulation experiments, the optical properties were assumed constant throughout the domain in this experiment. These values were also used as the optical properties at the emission wavelength. The hole was filled with a solution of 1% Intralipid to match the scattering value of the background, and varying concentrations of Lutex (0.3125 μM to 5 μM) were added. This represents a simple test case for investigating the imaging response to varying concentrations of fluorophore. The excitation source was a 690 nm laser diode which matches the wavelength used in the simulation studies. Total acquisition time for the fluorescence emission was less than 4 minutes (total of 240 data points).

*a*and

*b*, where

*y*is the measured intensity at a given wavelength pixel,

_{i}*F*and

*G*are the excitation and fluorescence basis spectra,

*a*and

*b*are the coefficients recovered in the minimization procedure, and

*N*is the number of wavelength pixels per spectrum. Once fit, the fluorescence signal is integrated and becomes the fluorescence emission intensity data for the reconstruction algorithm.

## 4. Results

### 4.1 Simulation results

### 4.2 Phantom results

_{a}and μ

_{s}’ were assumed known from prior measurements. In cases requiring the recovery of background optical properties, the improvement in reconstruction time will be similar to that previously quoted in the simulation results.

## 5. Discussion

30. B. Brooksby, B. W. Pogue, S. Jiang, H. Dehghani, S. Srinivasan, C. Kogel, T. D. Tosteson, J. Weaver, S. P. Poplack, and K. D. Paulsen, “Imaging breast adipose and fibroglandular tissue molecular signatures using hybrid MRI-guided near-infrared spectral tomography,” Proc. Natl. Acad. Sci. USA **103**,8828–8833 (2006). [CrossRef] [PubMed]

31. S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction,” Acad. Radiol. **13**,195–202 (2006). [CrossRef] [PubMed]

## 6. Conclusion

## Acknowledgments

## References

1. | D. Y. Paithankar, A. U. Chen, B. W. Pogue, M. S. Patterson, and E. M. Sevick-Muraca, “Imaging of fluorescent yeild and lifetime from multiply scattered light reemitted from random media,” Appl. Opt. |

2. | H. B. Jiang, “Frequency-domain fluorescent diffusion tomography: a finite- element-based algorithm and simulations,” Appl. Opt. |

3. | D. J. Hawrysz and E. M. Sevick-Muraca, “Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents,” Neoplasia |

4. | M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, “Three-dimensional, Bayesian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography,” Proc. Natl. Acad. Sci. USA |

5. | A. B. Milstein, O. Seungseok, K. J. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, “Fluorescence optical diffusion tomograhy,” Appl. Opt. |

6. | V. Ntziachristos and R. Weissleder, “Experimental three-dimensional fluorescence reconstruction of diffuse media by use of a normalized Born approximation,” Opt. Lett. |

7. | V. Ntziachristos and R. Weissleder, “Charge-coupled-device based scanner for tomography of fluorescent near-infrared probes in turbid media,” Med. Phys. |

8. | E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, “A submillimeter resolution fluorescence molecular imaging system for small animal imaging,” Med. Phys. |

9. | A. Godavarty, A. B. Thompson, R. Roy, M. Gurfinkel, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, “Diagnostic imaging of breast cancer using fluorescence-enhanced optical tomography: phantom studies,” J. Biomed. Opt. |

10. | R. B. Schulz, J. Ripoll, and V. Ntziachristos, “Experimental fluorescence tomography of tissue with noncontact measurements,” IEEE Trans. Med. Imaging |

11. | S. V. Patwardhan, S. R. Bloch, S. Achilefu, and J. P. Culver, “Time-dependent whole-body fluorescence tomography of probe bio-distribution in mice,” Opt. Exp. |

12. | A. Godavarty, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, “Detection of single and multiple targets in tissue phantoms with fluorescence-enhanced optical imaging: feasibility study,” Radiol. |

13. | B. Brooksby, S. Jiang, C. Kogel, M. Doyley, H. Dehghani, J. B. Weaver, S. P. Poplack, B. W. Pogue, and K. D. Paulsen, “Magnetic resonance-guided near-infrared tomography of the breast,” Rev. Sci. Instrum. |

14. | X. Intes, C. Maloux, M. Guven, B. Yazici, and B. Chance, “Diffuse Optical tomography with physiological and spatial a priori constraints,” Phys. Med. Biol. |

15. | M. Guven, B. Yazici, X. Intes, and B. Chance, “Diffuse optical tomography with a priori anatomical information,” Phys. Med. Biol. |

16. | P. K. Yalavarthy, H. Dehghani, B. W. Pogue, C. M. Carpenter, H. B. Jiang, and K. D. Paulsen, “Structural information within regularization matrices improves near infrared diffuse optical tomography,” IEEE Trans. Med. Imaging |

17. | G. Kostenich, A. Orenstein, L. Roitman, Z. Malik, and B. Ehrenberg, “In vivo photodynamic therapy with the new near-IR absorbing water soluble photosensitizer lutetium texaphyrin and a high intensity pulsed light delivery system,” Photochem. & Photobiol. |

18. | K. W. Woodburn, Q. Fan, D. R. Miles, D. Kessel, Y. Luo, and S. W. Young, “Localization and efficacy analysis of the phototherapeutic lutetium texaphyrin (PCI-0123) in the murine EMT6 sarcoma model,” Photochem. & Photobiol. |

19. | M. Zellweger, A. Radu, P. Monnier, H. van den Bergh, and G. Wagnieres, “Fluorescence pharmacokinetics of Lutetium Texaphyrin (PCI-0123, Lu-Tex) in the skin and in healthy and tumoral hamster cheek-pouch mucosa,” Photochem. & Photobiol. B |

20. | A. Synytsya, V. Kral, P. Matejka, P. Pouckova, K. Volka, and J. L. Sessler, “Biodistribution assessment of a lutetium(III) texaphyrin analogue in tumor-bearing mice using NIR Fourier-transform Raman spectroscopy,” Photochem. & Photobiol. |

21. | H. Dehghani, B. Brooksby, K. Vishwanath, B. W. Pogue, and P. K. D., “The effects of internal refractive index variation in near infrared optical tomography: A finite element modeling approach,” Phys. Med. Biol. |

22. | S. R. Arridge, M. Schweiger, M. Hiraoka, and D. T. Delpy, “A finite element approach for modeling photon transport in tissue,” Med. Phys. |

23. | K. D. Paulsen and H. Jiang, “Spatially varying optical property reconstruction using a finite element diffusion equation approximation,” Med. Phys. |

24. | S. R. Arridge and M. Schweiger, “Photon-measurement density functions. Part2: Finite-element-method calculations,” Appl. Opt. |

25. | A. Borsic, W. R. B. Lionheart, and C. N. McLeod, “Generation of anisotropic-smoothness regularization filters for EIT,” IEEE Trans. Med. Imaging |

26. | B. Brooksby, H. Dehghani, B. W. Pogue, and K. D. Paulsen, “Near infrared (NIR) tomography breast image reconstruction with a priori structural information from MRI: algorithm development for reconstructing heterogeneities,” IEEE J. STQE |

27. | K. D. Paulsen and H. Jiang, “Enhanced frequency-domain optical image reconstruction in tissues through total-variation minimization,” Appl. Opt. |

28. | K. D. Paulsen, P. Meaney, M. Moskowitz, and J. Sullican Jr., “A dual mesh for finite element based reconstruction algorithms,” IEEE Trans. Med. Imaging |

29. | M. Schweiger and S. R. Arridge, “Optical tomographic reconstruction in a complex head model using a priori boundary information,” Phys. Med. Biol. |

30. | B. Brooksby, B. W. Pogue, S. Jiang, H. Dehghani, S. Srinivasan, C. Kogel, T. D. Tosteson, J. Weaver, S. P. Poplack, and K. D. Paulsen, “Imaging breast adipose and fibroglandular tissue molecular signatures using hybrid MRI-guided near-infrared spectral tomography,” Proc. Natl. Acad. Sci. USA |

31. | S. Srinivasan, B. W. Pogue, S. Jiang, H. Dehghani, C. Kogel, S. Soho, J. J. Gibson, T. D. Tosteson, S. P. Poplack, and K. D. Paulsen, “In vivo hemoglobin and water concentrations, oxygen saturation, and scattering estimates from near-infrared breast tomography using spectral reconstruction,” Acad. Radiol. |

32. | T. O. McBride, B. W. Pogue, S. Jiang, U. L. Osterberg, K. D. Paulsen, and S. P. Poplack, “Initial studies of in vivo absorbing and scattering heterogeneity in near-infrared tomographic breast imaging,” Opt. Lett. |

33. | B. W. Pogue, T. O. McBride, J. Prewitt, U. L. Osterberg, and K. D. Paulsen, “Spatially variant regularization improves diffuse optical tomography,” Appl. Opt. |

34. | S. Jiang, B. W. Pogue, T. O. McBride, and K. D. Paulsen, “Quantitative analysis of near-infrared tomography: sensitivity to the tissue-simulating precalibration phantom,” J. Biomed. Opt. |

35. | B. Pogue and M. Patterson, “Review of tissue simulating phantoms for optical spectroscopy, imaging and dosimetry,” J. Biomed. Opt. |

**OCIS Codes**

(170.0110) Medical optics and biotechnology : Imaging systems

(170.1610) Medical optics and biotechnology : Clinical applications

(170.3010) Medical optics and biotechnology : Image reconstruction techniques

(170.6280) Medical optics and biotechnology : Spectroscopy, fluorescence and luminescence

(170.6960) Medical optics and biotechnology : Tomography

**ToC Category:**

Medical Optics and Biotechnology

**History**

Original Manuscript: January 4, 2007

Revised Manuscript: February 22, 2007

Manuscript Accepted: March 13, 2007

Published: April 2, 2007

**Virtual Issues**

Vol. 2, Iss. 5 *Virtual Journal for Biomedical Optics*

**Citation**

Scott C. Davis, Hamid Dehghani, Jia Wang, Shudong Jiang, Brian W. Pogue, and Keith D. Paulsen, "Image-guided diffuse optical fluorescence tomography implemented with Laplacian-type regularization," Opt. Express **15**, 4066-4082 (2007)

http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-15-7-4066

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### References

- D. Y. Paithankar, A. U. Chen, B. W. Pogue, M. S. Patterson, and E. M. Sevick-Muraca, "Imaging of fluorescent yeild and lifetime from multiply scattered light reemitted from random media," Appl. Opt. 36, 2260-2272 (1997). [CrossRef] [PubMed]
- H. B. Jiang, "Frequency-domain fluorescent diffusion tomography: a finite- element-based algorithm and simulations," Appl. Opt. 37, 5337-5343 (1998). [CrossRef]
- D. J. Hawrysz, and E. M. Sevick-Muraca, "Developments toward diagnostic breast cancer imaging using near-infrared optical measurements and fluorescent contrast agents," Neoplasia 2, 388-417 (2000). [CrossRef]
- M. J. Eppstein, D. J. Hawrysz, A. Godavarty, and E. M. Sevick-Muraca, "Three-dimensional, Bayesian image reconstruction from sparse and noisy data sets: near-infrared fluorescence tomography," Proc. Natl. Acad. Sci. USA 99, 9619-9624 (2002). [CrossRef] [PubMed]
- A. B. Milstein, O. Seungseok, K. J. Webb, C. A. Bouman, Q. Zhang, D. A. Boas, and R. P. Millane, "Fluorescence optical diffusion tomograhy," Appl. Opt. 42, 3081-3094 (2003). [CrossRef] [PubMed]
- V. Ntziachristos, and R. Weissleder, "Experimental three-dimensional fluorescence reconstruction of diffuse media by use of a normalized Born approximation," Opt. Lett. 26, 893-895 (2001). [CrossRef]
- V. Ntziachristos, and R. Weissleder, "Charge-coupled-device based scanner for tomography of fluorescent near-infrared probes in turbid media," Med. Phys. 29, 803-809 (2002). [CrossRef] [PubMed]
- E. Graves, J. Ripoll, R. Weissleder, and V. Ntziachristos, "A submillimeter resolution fluorescence molecular imaging system for small animal imaging," Med. Phys. 30, 901-911 (2003). [CrossRef] [PubMed]
- A. Godavarty, A. B. Thompson, R. Roy, M. Gurfinkel, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, "Diagnostic imaging of breast cancer using fluorescence-enhanced optical tomography: phantom studies," J. Biomed. Opt. 9, 488-496 (2004). [CrossRef] [PubMed]
- R. B. Schulz, J. Ripoll, and V. Ntziachristos, "Experimental fluorescence tomography of tissue with noncontact measurements," IEEE Trans. Med. Imaging 23, 492-500 (2004). [CrossRef] [PubMed]
- S. V. Patwardhan, S. R. Bloch, S. Achilefu, and J. P. Culver, "Time-dependent whole-body fluorescence tomography of probe bio-distribution in mice," Opt. Exp. 13, 2564-2577 (2005). [CrossRef]
- A. Godavarty, M. J. Eppstein, C. Zhang, and E. M. Sevick-Muraca, "Detection of single and multiple targets in tissue phantoms with fluorescence-enhanced optical imaging: feasibility study," Radiol. 235, 148-154 (2005). [CrossRef]
- B. Brooksby, S. Jiang, C. Kogel, M. Doyley, H. Dehghani, J. B. Weaver, S. P. Poplack, B. W. Pogue, and K. D. Paulsen, "Magnetic resonance-guided near-infrared tomography of the breast," Rev. Sci. Instrum. 75, 5262-5270 (2004). [CrossRef]
- X. Intes, C. Maloux, M. Guven, B. Yazici, and B. Chance, "Diffuse Optical tomography with physiological and spatial a priori constraints," Phys. Med. Biol. 49, N155-N163 (2004).</jrn> [CrossRef] [PubMed]
- M. Guven, B. Yazici, X. Intes, and B. Chance, "Diffuse optical tomography with a priori anatomical information," Phys. Med. Biol. 50, 2837-2858 (2005). [CrossRef] [PubMed]
- P. K. Yalavarthy, H. Dehghani, B. W. Pogue, C. M. Carpenter, H. B. Jiang, and K. D. Paulsen, "Structural information within regularization matrices improves near infrared diffuse optical tomography," IEEE Trans. Med. Imaging In review (2006).</other>
- G. Kostenich, A. Orenstein, L. Roitman, Z. Malik, and B. Ehrenberg, "In vivo photodynamic therapy with the new near-IR absorbing water soluble photosensitizer lutetium texaphyrin and a high intensity pulsed light delivery system," Photochem. & Photobiol. 39, 36-42 (1997). [CrossRef]
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