Abstract

We model the capability of a small (6-optode) time-resolved diffuse optical tomography (DOT) system to infer baseline absorption and reduced scattering coefficients of the tissues of the human head (scalp, skull, and brain). Our heterogeneous three-dimensional diffusion forward model uses tissue geometry from segmented magnetic resonance (MR) data. Handling the inverse problem by use of Bayesian inference and introducing a realistic noise model, we predict coefficient error bars in terms of detected photon number and assumed model error. We demonstrate the large improvement that a MR-segmented model can provide: 2–10% error in brain coefficients (for 2 × 106 photons, 5% model error). We sample from the exact posterior and show robustness to numerical model error. This opens up the possibility of simultaneous DOT and MR for quantitative cortically constrained functional neuroimaging.

© 2003 Optical Society of America

Full Article  |  PDF Article

References

  • View by:
  • |
  • |
  • |

  1. D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
    [CrossRef]
  2. B. Chance, D. T. Delpy, C. E. Cooper, E. O. R. Reynolds, eds., “Near-infrared spectroscopy and imaging of living systems,” Philos. Trans. R. Soc. London Ser. B 352, 649–763 (1997)
  3. D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.
  4. A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
    [CrossRef] [PubMed]
  5. S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
    [CrossRef]
  6. B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).
  7. J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
    [CrossRef]
  8. N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
    [CrossRef] [PubMed]
  9. S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
    [CrossRef]
  10. A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
    [CrossRef]
  11. G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
    [CrossRef] [PubMed]
  12. J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
    [CrossRef] [PubMed]
  13. V. Ntziachristos, A. G. Yodh, M. Schnall, B. Chance, “Concurrent MRI and diffuse optical tomography of breast after indocyanine green enhancement,” Proc. Natl. Acad. Sci. USA 97, 2767–2772 (2000).
    [CrossRef] [PubMed]
  14. G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
    [CrossRef] [PubMed]
  15. S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
    [CrossRef]
  16. D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
    [CrossRef] [PubMed]
  17. S. Wray, M. Cope, D. T. Delpy, “Characteristics of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation,” Biochim. Biophys. Acta 933, 184–192 (1988).
    [CrossRef] [PubMed]
  18. W. D. Heiss, “Ischemic penumbra: evidence from functional imaging in man,” J. Cereb. Blood Flow Metab. 20, 1276–1793 (2000).
    [CrossRef] [PubMed]
  19. S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
    [CrossRef] [PubMed]
  20. S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
    [CrossRef] [PubMed]
  21. R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.
  22. A. J. Devaney, “Reconstruction tomography with diffractive wave-fields,” Inverse Probl. 2, 161–183 (1986).
    [CrossRef]
  23. S. R. Arridge, J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42, 841–854 (1997).
    [CrossRef] [PubMed]
  24. X. Cheng, D. A. Boas, “Systematic diffuse optical image errors resulting from uncertainty in the background optical properties,” Opt. Exp. 4, 299–307 (1999); http://www.opticsexpress.org .
    [CrossRef]
  25. V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
    [CrossRef] [PubMed]
  26. S. R. Arridge, M. Schweiger, “Reconstruction in optical tomography using MRI based prior knowledge,” in Information Processing in Medical Imaging, Y. Bizais, C. Barillot, R. di Paola, eds. (Kluwer, Dordrecht, The Netherlands, 1995), pp. 77–88.
  27. M. Schweiger, S. R. Arridge, “Optical tomographic reconstruction in a complex head model using a priori region boundary information,” Phys. Med. Biol. 44, 2703–2722 (1999).
    [CrossRef] [PubMed]
  28. M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
    [CrossRef]
  29. J. D. Oakley, “Magnetic resonance imaging based correction and reconstruction of positron emission tomography images,” Ph.D. dissertation (Service Hospitalier Frederic Joliot, CEA, Orsay, France, 2000).
  30. V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
    [CrossRef]
  31. M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
    [CrossRef]
  32. M. S. Patterson, B. Chance, B. C. Wilson, “Time-resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties,” Appl. Opt. 28, 2331–2336 (1989).
    [CrossRef] [PubMed]
  33. R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, G. Valentini, “Time-resolved imaging on a realistic tissue phantom: μs′ and μa images versus time-integrated images,” Appl. Opt. 35, 4533–4540 (1996).
    [CrossRef] [PubMed]
  34. A. Torricelli, A. Pifferi, P. Taroni, E. Giambattistelli, R. Cubeddu, “In vivo optical characterization of human tissues from 610 to 1010 nm by time-resolved reflectance spectroscopy,” Phys. Med. Biol. 46, 2227–2237 (2001).
    [CrossRef] [PubMed]
  35. A. Kienle, M. S. Patterson, N. Dögnitz, R. Bays, G. Wagnières, H. van den Bergh, “Noninvasive determination of the optical properties of two-layered media,” Appl. Opt. 37, 779–791 (1998).
    [CrossRef]
  36. A. Kienle, T. Glanzmann, G. Wagnières, H. van den Bergh, “Investigation of two-layered turbid media with time-resolved reflectance,” Appl. Opt. 37, 6852–6862 (1998).
    [CrossRef]
  37. A. Pifferi, A. Torricelli, P. Taroni, R. Cubeddu, “Reconstruction of absorber concentrations in a two-layer structure by use of multidistance time-resolved reflectance spectroscopy,” Opt. Lett. 26, 1963–1965 (2001).
    [CrossRef]
  38. C. K. Hayakawa, J. Spanier, F. Bevilacqua, A. K. Dunn, J. S. You, B. J. Tromberg, V. Venugopalan, “Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues,” Opt. Lett. 26, 1335–1337 (2001).
    [CrossRef]
  39. A. Kienle, T. Glanzmann, “In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model,” Phys. Med. Biol. 44, 2689–2702 (1999).
    [CrossRef] [PubMed]
  40. K. M. Hanson, G. S. Cunningham, S. S. Saquib, “Inversion based on computational simulations,” in Maximum Entropy and Bayesian Methods, G. J. Erickson, J. T. Rychert, C. R. Smith, eds. (Kluwer Academic, Dordrecht, The Netherlands, 1998), pp. 121–135.
    [CrossRef]
  41. S. S. Saquib, K. M. Hanson, G. S. Cunningham, “Model-based image reconstruction from time-resolved diffusion data,” in Medical Imaging 1997: Image Processing, K. M. Hanson, ed., Proc. SPIE3034, 369–380 (1997).
    [CrossRef]
  42. G. Nicholls, C. Fox, “Prior modelling and posterior sampling in impedance imaging,” in Bayesian Inference for Inverse Problems, A. Mohammad-Djafari, ed., Proc. SPIE3459, 116–127 (1998).
    [CrossRef]
  43. J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
    [CrossRef]
  44. D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
    [CrossRef] [PubMed]
  45. S. Oh, A. B. Milstein, R. P. Millane, C. A. Bouman, K. J. Webb, “Source–detector calibration in three-dimensional Bayesian optical diffusion tomography,” J. Opt. Soc. Am. A 19, 1983–1993 (2002).
    [CrossRef]
  46. I. Kwee, “Towards a Bayesian framework for optical tomography,” Ph.D. dissertation (Department of Medical Physics and Bioengineering, University College London, London, 1999).
  47. M. J. Eppstein, D. E. Dougherty, T. L. Troy, E. M. Sevick-Muraca, “Biomedical optical tomography using dynamic parameterization and Bayesian conditioning on photon migration measurements,” Appl. Opt. 38, 2138–2150 (1999).
    [CrossRef]
  48. K. J. Friston, “Bayesian estimation of dynamical systems: an application to fMRI,” NeuroImage 16, 513–530 (2002).
    [CrossRef] [PubMed]
  49. D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
    [CrossRef]
  50. D. J. C. MacKay, “Information theory, inference, and learning algorithms,” Chap. 3, available at http://www.inference.phy.cam.ac.uk/mackay/book.html .
  51. J. Berger, Statistical Decision Theory and Bayesian Analysis (Springer, New York, 1985).
    [CrossRef]
  52. S. J. Press, Bayesian Statistics: Principles, Models, and Applications, Wiley Series in Probability and Statistics (Wiley, New York, 1989).
  53. D. S. Sivia, Data Analysis: A Bayesian Tutorial (Oxford U. Press, Oxford, U.K., 1996).
  54. S. F. Gull, “Bayesian inductive inference and maximum entropy,” in Foundations, Vol. 1 of Maximum Entropy and Bayesian Methods in Science and Engineering, G. R. Erickson, C. R. Smith, eds. (Kluwer, Dordrecht, The Netherlands, 1988).
    [CrossRef]
  55. R. M. Neal, “Probabilistic inference using Markov chain Monte Carlo methods,” Tech. Rep. CRG-TR-93-1 (Department of Computer Science, University of Toronto, Toronto, 1993); available at http://www.cs.toronto.edu/∼radford/review.abstract.html .
  56. S. R. Arridge, M. Schweiger, “A gradient-based optimisation scheme for optical tomography,” Opt. Exp. 2, 213–226 (1998); http://www.opticsexpress.org .
    [CrossRef]
  57. A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
    [CrossRef] [PubMed]
  58. F. Gao, H. Zhao, Y. Yamada, “Improvement of image quality in diffuse optical tomography by use of full time-resolved data,” Appl. Opt. 41, 778–791 (2002).
    [CrossRef] [PubMed]
  59. A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
    [CrossRef] [PubMed]
  60. E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
    [CrossRef] [PubMed]
  61. F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38, 4939–4950 (1999).
    [CrossRef]
  62. J. C. Tamraz, Y. G. Comair, Atlas of Regional Anatomy of the Brain Using MRI: With Functional Correlations (Springer, New York, 2000).
  63. J. Ripoll, S. R. Arridge, M. Nieto-Vesperinas, “Effect of roughness in nondiffusive regions within diffusive media,” J. Opt. Soc. Am. A 18, 940–947 (2001).
    [CrossRef]
  64. F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
    [CrossRef]
  65. K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
    [CrossRef] [PubMed]
  66. A. Ishimaru, Wave Propagation and Scattering in Random Media (Academic, New York, 1978), Vol. 1.
  67. A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998).
    [CrossRef] [PubMed]
  68. T. B. Durduran, B. Chance, A. G. Yodh, D. A. Boas, “Does the photon diffusion coefficient depend on absorption?,” J. Opt. Soc. Am. A 14, 3358–3365 (1997).
    [CrossRef]
  69. Note that for us this acronym does not imply association with hyperbolic equations. We are evolving a parabolic equation.
  70. H. Dehghani, S. R. Arridge, M. Schweiger, D. T. Delpy, “Optical tomography in the presence of void regions,” J. Opt. Soc. Am. A 17, 1659–1670 (2000).
    [CrossRef]
  71. S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
    [CrossRef] [PubMed]
  72. W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .
  73. S. J. Press, Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Interference, 2nd ed. (Krieger, Malabar, Fla., 1982).
  74. R. D. Richtmeyer, K. W. Morton, Difference Methods for Initial-Value Problems (Wiley, New York, 1967).
  75. J. W. Thomas, Numerical Partial Differential Equations: Finite Difference Methods (Springer-Verlag, New York, 1995).

2002 (5)

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

S. Oh, A. B. Milstein, R. P. Millane, C. A. Bouman, K. J. Webb, “Source–detector calibration in three-dimensional Bayesian optical diffusion tomography,” J. Opt. Soc. Am. A 19, 1983–1993 (2002).
[CrossRef]

K. J. Friston, “Bayesian estimation of dynamical systems: an application to fMRI,” NeuroImage 16, 513–530 (2002).
[CrossRef] [PubMed]

F. Gao, H. Zhao, Y. Yamada, “Improvement of image quality in diffuse optical tomography by use of full time-resolved data,” Appl. Opt. 41, 778–791 (2002).
[CrossRef] [PubMed]

2001 (10)

J. Ripoll, S. R. Arridge, M. Nieto-Vesperinas, “Effect of roughness in nondiffusive regions within diffusive media,” J. Opt. Soc. Am. A 18, 940–947 (2001).
[CrossRef]

D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
[CrossRef]

A. Torricelli, A. Pifferi, P. Taroni, E. Giambattistelli, R. Cubeddu, “In vivo optical characterization of human tissues from 610 to 1010 nm by time-resolved reflectance spectroscopy,” Phys. Med. Biol. 46, 2227–2237 (2001).
[CrossRef] [PubMed]

A. Pifferi, A. Torricelli, P. Taroni, R. Cubeddu, “Reconstruction of absorber concentrations in a two-layer structure by use of multidistance time-resolved reflectance spectroscopy,” Opt. Lett. 26, 1963–1965 (2001).
[CrossRef]

C. K. Hayakawa, J. Spanier, F. Bevilacqua, A. K. Dunn, J. S. You, B. J. Tromberg, V. Venugopalan, “Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues,” Opt. Lett. 26, 1335–1337 (2001).
[CrossRef]

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

2000 (8)

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

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

W. D. Heiss, “Ischemic penumbra: evidence from functional imaging in man,” J. Cereb. Blood Flow Metab. 20, 1276–1793 (2000).
[CrossRef] [PubMed]

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

H. Dehghani, S. R. Arridge, M. Schweiger, D. T. Delpy, “Optical tomography in the presence of void regions,” J. Opt. Soc. Am. A 17, 1659–1670 (2000).
[CrossRef]

1999 (10)

F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38, 4939–4950 (1999).
[CrossRef]

A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
[CrossRef] [PubMed]

A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
[CrossRef] [PubMed]

D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
[CrossRef] [PubMed]

M. J. Eppstein, D. E. Dougherty, T. L. Troy, E. M. Sevick-Muraca, “Biomedical optical tomography using dynamic parameterization and Bayesian conditioning on photon migration measurements,” Appl. Opt. 38, 2138–2150 (1999).
[CrossRef]

A. Kienle, T. Glanzmann, “In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model,” Phys. Med. Biol. 44, 2689–2702 (1999).
[CrossRef] [PubMed]

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

X. Cheng, D. A. Boas, “Systematic diffuse optical image errors resulting from uncertainty in the background optical properties,” Opt. Exp. 4, 299–307 (1999); http://www.opticsexpress.org .
[CrossRef]

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
[CrossRef]

1998 (5)

1997 (7)

T. B. Durduran, B. Chance, A. G. Yodh, D. A. Boas, “Does the photon diffusion coefficient depend on absorption?,” J. Opt. Soc. Am. A 14, 3358–3365 (1997).
[CrossRef]

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[CrossRef] [PubMed]

S. R. Arridge, J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42, 841–854 (1997).
[CrossRef] [PubMed]

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

B. Chance, D. T. Delpy, C. E. Cooper, E. O. R. Reynolds, eds., “Near-infrared spectroscopy and imaging of living systems,” Philos. Trans. R. Soc. London Ser. B 352, 649–763 (1997)

A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
[CrossRef] [PubMed]

D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
[CrossRef] [PubMed]

1996 (1)

1995 (2)

S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
[CrossRef] [PubMed]

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

1993 (1)

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

1990 (1)

K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
[CrossRef] [PubMed]

1989 (1)

1988 (1)

S. Wray, M. Cope, D. T. Delpy, “Characteristics of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation,” Biochim. Biophys. Acta 933, 184–192 (1988).
[CrossRef] [PubMed]

1986 (1)

A. J. Devaney, “Reconstruction tomography with diffractive wave-fields,” Inverse Probl. 2, 161–183 (1986).
[CrossRef]

Alcouffe, R. E.

A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998).
[CrossRef] [PubMed]

Alfano, R. R.

K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
[CrossRef] [PubMed]

Aronson, R.

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

Arridge, S. R.

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

J. Ripoll, S. R. Arridge, M. Nieto-Vesperinas, “Effect of roughness in nondiffusive regions within diffusive media,” J. Opt. Soc. Am. A 18, 940–947 (2001).
[CrossRef]

D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
[CrossRef]

H. Dehghani, S. R. Arridge, M. Schweiger, D. T. Delpy, “Optical tomography in the presence of void regions,” J. Opt. Soc. Am. A 17, 1659–1670 (2000).
[CrossRef]

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

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

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
[CrossRef]

S. R. Arridge, M. Schweiger, “A gradient-based optimisation scheme for optical tomography,” Opt. Exp. 2, 213–226 (1998); http://www.opticsexpress.org .
[CrossRef]

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[CrossRef] [PubMed]

S. R. Arridge, J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42, 841–854 (1997).
[CrossRef] [PubMed]

S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
[CrossRef] [PubMed]

S. R. Arridge, M. Schweiger, “Reconstruction in optical tomography using MRI based prior knowledge,” in Information Processing in Medical Imaging, Y. Bizais, C. Barillot, R. di Paola, eds. (Kluwer, Dordrecht, The Netherlands, 1995), pp. 77–88.

Barbieri, B.

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Barbour, R.

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

Barbour, R. L.

A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998).
[CrossRef] [PubMed]

Bays, R.

Benaron, D. A.

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Berger, J.

J. Berger, Statistical Decision Theory and Bayesian Analysis (Springer, New York, 1985).
[CrossRef]

Beuthan, J.

A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
[CrossRef]

Bevilacqua, F.

Boas, D. A.

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
[CrossRef]

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

X. Cheng, D. A. Boas, “Systematic diffuse optical image errors resulting from uncertainty in the background optical properties,” Opt. Exp. 4, 299–307 (1999); http://www.opticsexpress.org .
[CrossRef]

D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
[CrossRef] [PubMed]

T. B. Durduran, B. Chance, A. G. Yodh, D. A. Boas, “Does the photon diffusion coefficient depend on absorption?,” J. Opt. Soc. Am. A 14, 3358–3365 (1997).
[CrossRef]

D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.

Bouman, C. A.

Brooks, D.

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

Brooks, D. H.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

Butler, J.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Cerussi, A.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Chance, B.

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

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

A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
[CrossRef] [PubMed]

D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
[CrossRef] [PubMed]

T. B. Durduran, B. Chance, A. G. Yodh, D. A. Boas, “Does the photon diffusion coefficient depend on absorption?,” J. Opt. Soc. Am. A 14, 3358–3365 (1997).
[CrossRef]

M. S. Patterson, B. Chance, B. C. Wilson, “Time-resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties,” Appl. Opt. 28, 2331–2336 (1989).
[CrossRef] [PubMed]

Chang, J.

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

Cheng, X.

X. Cheng, D. A. Boas, “Systematic diffuse optical image errors resulting from uncertainty in the background optical properties,” Opt. Exp. 4, 299–307 (1999); http://www.opticsexpress.org .
[CrossRef]

Cheong, W.-F.

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Comair, Y. G.

J. C. Tamraz, Y. G. Comair, Atlas of Regional Anatomy of the Brain Using MRI: With Functional Correlations (Springer, New York, 2000).

Cope, M.

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[CrossRef] [PubMed]

S. Wray, M. Cope, D. T. Delpy, “Characteristics of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation,” Biochim. Biophys. Acta 933, 184–192 (1988).
[CrossRef] [PubMed]

Corballis, P. M.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Cubeddu, R.

Culver, J. P.

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

Cunningham, G. S.

K. M. Hanson, G. S. Cunningham, S. S. Saquib, “Inversion based on computational simulations,” in Maximum Entropy and Bayesian Methods, G. J. Erickson, J. T. Rychert, C. R. Smith, eds. (Kluwer Academic, Dordrecht, The Netherlands, 1998), pp. 121–135.
[CrossRef]

S. S. Saquib, K. M. Hanson, G. S. Cunningham, “Model-based image reconstruction from time-resolved diffusion data,” in Medical Imaging 1997: Image Processing, K. M. Hanson, ed., Proc. SPIE3034, 369–380 (1997).
[CrossRef]

Curio, G.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Dale, A. M.

A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
[CrossRef] [PubMed]

Dehghani, H.

Delpy, D. T.

Depeursinge, C.

Devaney, A. J.

A. J. Devaney, “Reconstruction tomography with diffractive wave-fields,” Inverse Probl. 2, 161–183 (1986).
[CrossRef]

DiMarzio, C. A.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

Dögnitz, N.

Dougherty, D. E.

Dunn, A. K.

C. K. Hayakawa, J. Spanier, F. Bevilacqua, A. K. Dunn, J. S. You, B. J. Tromberg, V. Venugopalan, “Perturbation Monte Carlo methods to solve inverse photon migration problems in heterogeneous tissues,” Opt. Lett. 26, 1335–1337 (2001).
[CrossRef]

D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.

Durduran, T. B.

Eker, C.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Eppstein, M. J.

Espinoza, J.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Fabiani, M.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Fantini, S.

S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
[CrossRef]

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Firbank, M.

Fischl, B.

A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
[CrossRef] [PubMed]

Fishkin, J.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Flannery, B. P.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .

Fox, C.

G. Nicholls, C. Fox, “Prior modelling and posterior sampling in impedance imaging,” in Bayesian Inference for Inverse Problems, A. Mohammad-Djafari, ed., Proc. SPIE3459, 116–127 (1998).
[CrossRef]

Franceschini, M. A.

S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
[CrossRef]

D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.

Franceschini-Fantini, M. A.

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Friedman, D.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Friston, K. J.

K. J. Friston, “Bayesian estimation of dynamical systems: an application to fMRI,” NeuroImage 16, 513–530 (2002).
[CrossRef] [PubMed]

Fry, M. E.

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

Gao, F.

Gaudette, R. J.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

Gaudette, T. J.

D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
[CrossRef]

George, J. S.

D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
[CrossRef] [PubMed]

Giambattistelli, E.

A. Torricelli, A. Pifferi, P. Taroni, E. Giambattistelli, R. Cubeddu, “In vivo optical characterization of human tissues from 610 to 1010 nm by time-resolved reflectance spectroscopy,” Phys. Med. Biol. 46, 2227–2237 (2001).
[CrossRef] [PubMed]

Glanzmann, T.

A. Kienle, T. Glanzmann, “In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model,” Phys. Med. Biol. 44, 2689–2702 (1999).
[CrossRef] [PubMed]

A. Kienle, T. Glanzmann, G. Wagnières, H. van den Bergh, “Investigation of two-layered turbid media with time-resolved reflectance,” Appl. Opt. 37, 6852–6862 (1998).
[CrossRef]

Goodman-Wood, M. R.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Graber, H.

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

Gratton, E.

S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
[CrossRef]

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Gratton, G.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Gross, J. D.

Gull, S. F.

S. F. Gull, “Bayesian inductive inference and maximum entropy,” in Foundations, Vol. 1 of Maximum Entropy and Bayesian Methods in Science and Engineering, G. R. Erickson, C. R. Smith, eds. (Kluwer, Dordrecht, The Netherlands, 1988).
[CrossRef]

Hämäläinen, M.

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Hanson, K. M.

A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
[CrossRef] [PubMed]

K. M. Hanson, G. S. Cunningham, S. S. Saquib, “Inversion based on computational simulations,” in Maximum Entropy and Bayesian Methods, G. J. Erickson, J. T. Rychert, C. R. Smith, eds. (Kluwer Academic, Dordrecht, The Netherlands, 1998), pp. 121–135.
[CrossRef]

S. S. Saquib, K. M. Hanson, G. S. Cunningham, “Model-based image reconstruction from time-resolved diffusion data,” in Medical Imaging 1997: Image Processing, K. M. Hanson, ed., Proc. SPIE3034, 369–380 (1997).
[CrossRef]

A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
[CrossRef]

Hari, R.

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Hayakawa, C. K.

Hebden, J. C.

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

S. R. Arridge, J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42, 841–854 (1997).
[CrossRef] [PubMed]

Heiss, W. D.

W. D. Heiss, “Ischemic penumbra: evidence from functional imaging in man,” J. Cereb. Blood Flow Metab. 20, 1276–1793 (2000).
[CrossRef] [PubMed]

Hielscher, A. H.

A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
[CrossRef] [PubMed]

A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998).
[CrossRef] [PubMed]

A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
[CrossRef]

Hillman, E. M. C.

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

Hintz, S. R.

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Hiraoka, M.

S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
[CrossRef] [PubMed]

Hirsch, J.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Hood, D. C.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Hornung, R.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Ilmoniemi, R.

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Ishimaru, A.

A. Ishimaru, Wave Propagation and Scattering in Random Media (Academic, New York, 1978), Vol. 1.

Kaipio, J. P.

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

Kaschke, M.

Kienle, A.

Kilmer, M.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

Kim, K.

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

Klose, A.

A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
[CrossRef]

Klose, A. D.

A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
[CrossRef] [PubMed]

Knuutila, J.

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Kohl, M.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Kolehmainen, V.

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

Kwee, I.

I. Kwee, “Towards a Bayesian framework for optical tomography,” Ph.D. dissertation (Department of Medical Physics and Bioengineering, University College London, London, 1999).

Liu, F.

K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
[CrossRef] [PubMed]

Lounasmaa, O. V.

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Maier, J. S.

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Marquet, P.

McBride, T. O.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Millane, R. P.

Miller, E.

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

Miller, E. L.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

Milstein, A. B.

Moesta, K. T.

Morton, K. W.

R. D. Richtmeyer, K. W. Morton, Difference Methods for Initial-Value Problems (Wiley, New York, 1967).

Neal, R. M.

R. M. Neal, “Probabilistic inference using Markov chain Monte Carlo methods,” Tech. Rep. CRG-TR-93-1 (Department of Computer Science, University of Toronto, Toronto, 1993); available at http://www.cs.toronto.edu/∼radford/review.abstract.html .

Nicholls, G.

G. Nicholls, C. Fox, “Prior modelling and posterior sampling in impedance imaging,” in Bayesian Inference for Inverse Problems, A. Mohammad-Djafari, ed., Proc. SPIE3459, 116–127 (1998).
[CrossRef]

Nieto-Vesperinas, M.

Ntziachristos, V.

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

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

O’Leary, M. A.

Oakley, J. D.

J. D. Oakley, “Magnetic resonance imaging based correction and reconstruction of positron emission tomography images,” Ph.D. dissertation (Service Hospitalier Frederic Joliot, CEA, Orsay, France, 2000).

Obrig, H.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Oh, S.

Okada, E.

Osterberg, U.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Osterman, S.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Patterson, M. S.

Paulsen, K. D.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Pifferi, A.

Piguet, D.

Pogue, B. W.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Poplack, S.

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Press, S. J.

S. J. Press, Bayesian Statistics: Principles, Models, and Applications, Wiley Series in Probability and Statistics (Wiley, New York, 1989).

S. J. Press, Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Interference, 2nd ed. (Krieger, Malabar, Fla., 1982).

Press, W. H.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .

Richtmeyer, R. D.

R. D. Richtmeyer, K. W. Morton, Difference Methods for Initial-Value Problems (Wiley, New York, 1967).

Rinneberg, H.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Ripoll, J.

Saquib, S. S.

K. M. Hanson, G. S. Cunningham, S. S. Saquib, “Inversion based on computational simulations,” in Maximum Entropy and Bayesian Methods, G. J. Erickson, J. T. Rychert, C. R. Smith, eds. (Kluwer Academic, Dordrecht, The Netherlands, 1998), pp. 121–135.
[CrossRef]

S. S. Saquib, K. M. Hanson, G. S. Cunningham, “Model-based image reconstruction from time-resolved diffusion data,” in Medical Imaging 1997: Image Processing, K. M. Hanson, ed., Proc. SPIE3034, 369–380 (1997).
[CrossRef]

Schlag, P. M.

Schmidt, D. M.

D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
[CrossRef] [PubMed]

Schmidt, F. E.

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

Schnall, M.

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

Schnall, M. D.

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

Schweiger, M.

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

H. Dehghani, S. R. Arridge, M. Schweiger, D. T. Delpy, “Optical tomography in the presence of void regions,” J. Opt. Soc. Am. A 17, 1659–1670 (2000).
[CrossRef]

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

S. R. Arridge, M. Schweiger, “A gradient-based optimisation scheme for optical tomography,” Opt. Exp. 2, 213–226 (1998); http://www.opticsexpress.org .
[CrossRef]

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[CrossRef] [PubMed]

S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
[CrossRef] [PubMed]

S. R. Arridge, M. Schweiger, “Reconstruction in optical tomography using MRI based prior knowledge,” in Information Processing in Medical Imaging, Y. Bizais, C. Barillot, R. di Paola, eds. (Kluwer, Dordrecht, The Netherlands, 1995), pp. 77–88.

Sereno, M. I.

A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
[CrossRef] [PubMed]

Sevick-Muraca, E. M.

Shah, N.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Siegel, A. M.

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

Sivia, D. S.

D. S. Sivia, Data Analysis: A Bayesian Tutorial (Oxford U. Press, Oxford, U.K., 1996).

Somersalo, E.

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

Spanier, J.

Steinbrink, J.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Stevenson, D. K.

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Strangman, G.

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.

Syre, F.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Tamraz, J. C.

J. C. Tamraz, Y. G. Comair, Atlas of Regional Anatomy of the Brain Using MRI: With Functional Correlations (Springer, New York, 2000).

Taroni, P.

Teukolsky, S. A.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .

Thomas, F.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Thomas, J. W.

J. W. Thomas, Numerical Partial Differential Equations: Finite Difference Methods (Springer-Verlag, New York, 1995).

Thompson, J. H.

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

Torricelli, A.

Tromberg, B.

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

Tromberg, B. J.

Troy, T. L.

Valentini, G.

van den Bergh, H.

van Houten, J. P.

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Vauhkonen, M.

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

Veenstra, H.

Venugopalan, V.

Vetterling, W. T.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .

Villringer, A.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
[CrossRef] [PubMed]

Wabnitz, H.

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Wagnières, G.

Walker, S. A.

S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
[CrossRef]

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Wang, Y.

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

Webb, K. J.

Wilson, B. C.

Wood, C. C.

D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
[CrossRef] [PubMed]

Wray, S.

S. Wray, M. Cope, D. T. Delpy, “Characteristics of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation,” Biochim. Biophys. Acta 933, 184–192 (1988).
[CrossRef] [PubMed]

Yamada, Y.

Yodh, A. G.

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

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

D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
[CrossRef] [PubMed]

T. B. Durduran, B. Chance, A. G. Yodh, D. A. Boas, “Does the photon diffusion coefficient depend on absorption?,” J. Opt. Soc. Am. A 14, 3358–3365 (1997).
[CrossRef]

Yoo, K. M.

K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
[CrossRef] [PubMed]

You, J. S.

Zhang, Q.

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

Zhao, H.

Zourabian, A.

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

Appl. Opt. (11)

S. Fantini, S. A. Walker, M. A. Franceschini, K. T. Moesta, P. M. Schlag, M. Kaschke, E. Gratton, “Assessment of the size, position, and optical properties of breast tumors in vivo by noninvasive optical methods,” Appl. Opt. 37, 1982–1989 (1998).
[CrossRef]

J. C. Hebden, H. Veenstra, H. Dehghani, E. M. C. Hillman, M. Schweiger, S. R. Arridge, D. T. Delpy, “Three-dimensional time-resolved optical tomography of a conical breast phantom,” Appl. Opt. 40, 3278–3287 (2001).
[CrossRef]

D. A. Boas, M. A. O’Leary, B. Chance, A. G. Yodh, “Detection and characterization of optical inhomogeneities with diffuse photon density waves: a signal-to-noise analysis,” Appl. Opt. 36, 75–92 (1997).
[CrossRef] [PubMed]

A. Kienle, M. S. Patterson, N. Dögnitz, R. Bays, G. Wagnières, H. van den Bergh, “Noninvasive determination of the optical properties of two-layered media,” Appl. Opt. 37, 779–791 (1998).
[CrossRef]

A. Kienle, T. Glanzmann, G. Wagnières, H. van den Bergh, “Investigation of two-layered turbid media with time-resolved reflectance,” Appl. Opt. 37, 6852–6862 (1998).
[CrossRef]

M. S. Patterson, B. Chance, B. C. Wilson, “Time-resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties,” Appl. Opt. 28, 2331–2336 (1989).
[CrossRef] [PubMed]

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, G. Valentini, “Time-resolved imaging on a realistic tissue phantom: μs′ and μa images versus time-integrated images,” Appl. Opt. 35, 4533–4540 (1996).
[CrossRef] [PubMed]

M. J. Eppstein, D. E. Dougherty, T. L. Troy, E. M. Sevick-Muraca, “Biomedical optical tomography using dynamic parameterization and Bayesian conditioning on photon migration measurements,” Appl. Opt. 38, 2138–2150 (1999).
[CrossRef]

F. Gao, H. Zhao, Y. Yamada, “Improvement of image quality in diffuse optical tomography by use of full time-resolved data,” Appl. Opt. 41, 778–791 (2002).
[CrossRef] [PubMed]

E. Okada, M. Firbank, M. Schweiger, S. R. Arridge, M. Cope, D. T. Delpy, “Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head,” Appl. Opt. 36, 21–31 (1997).
[CrossRef] [PubMed]

F. Bevilacqua, D. Piguet, P. Marquet, J. D. Gross, B. J. Tromberg, C. Depeursinge, “In vivo local determination of tissue optical properties: applications to human brain,” Appl. Opt. 38, 4939–4950 (1999).
[CrossRef]

Biochim. Biophys. Acta (1)

S. Wray, M. Cope, D. T. Delpy, “Characteristics of the near infrared absorption spectra of cytochrome aa3 and hemoglobin for the noninvasive monitoring of cerebral oxygenation,” Biochim. Biophys. Acta 933, 184–192 (1988).
[CrossRef] [PubMed]

Hum. Brain Mapp. (1)

D. M. Schmidt, J. S. George, C. C. Wood, “Bayesian inference applied to the electromagnetic inverse problem,” Hum. Brain Mapp. 7, 195–212 (1999).
[CrossRef] [PubMed]

IEEE Signal Process. Mag. (1)

D. A. Boas, D. H. Brooks, E. L. Miller, C. A. DiMarzio, M. Kilmer, R. J. Gaudette, Q. Zhang, “Imaging the body with diffuse optical tomography,” IEEE Signal Process. Mag. 18(6), 57–75 (2001).
[CrossRef]

IEEE Trans. Med. Imaging (1)

A. H. Hielscher, A. D. Klose, K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography,” IEEE Trans. Med. Imaging 18, 262–271 (1999).
[CrossRef] [PubMed]

Inverse Probl. (3)

J. P. Kaipio, V. Kolehmainen, E. Somersalo, M. Vauhkonen, “Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography,” Inverse Probl. 16, 1487–1522 (2000).
[CrossRef]

A. J. Devaney, “Reconstruction tomography with diffractive wave-fields,” Inverse Probl. 2, 161–183 (1986).
[CrossRef]

S. R. Arridge, “Optical tomography in medical imaging,” Inverse Probl. 15, R41–R93 (1999).
[CrossRef]

J. Cereb. Blood Flow Metab. (1)

W. D. Heiss, “Ischemic penumbra: evidence from functional imaging in man,” J. Cereb. Blood Flow Metab. 20, 1276–1793 (2000).
[CrossRef] [PubMed]

J. Opt. Soc. Am. A (4)

J. Perinat. Med. (1)

S. R. Hintz, D. A. Benaron, A. M. Siegel, A. Zourabian, D. K. Stevenson, D. A. Boas, “Bedside functional imaging of the premature infant brain during passive motor activation,” J. Perinat. Med. 29, 335–343 (2001).
[CrossRef] [PubMed]

Neoplasia (1)

V. Ntziachristos, A. G. Yodh, M. D. Schnall, B. Chance, “MRI-guided diffuse optical spectroscopy of malignant and benign breast lesions,” Neoplasia 4, 347–354 (2002).
[CrossRef] [PubMed]

NeuroImage (4)

G. Gratton, M. Fabiani, P. M. Corballis, D. C. Hood, M. R. Goodman-Wood, J. Hirsch, K. Kim, D. Friedman, E. Gratton, “Fast and localized event-related optical signals (EROS) in the human occipital cortex: comparisons with the visual evoked potential and fMRI,” NeuroImage 6, 168–180 (1997).
[CrossRef] [PubMed]

G. Strangman, J. P. Culver, J. H. Thompson, D. A. Boas, “A quantitative comparison of simultaneous BOLD fMRI and NIRS recordings during functional brain activation,” NeuroImage 17, 719–731 (2002).
[CrossRef] [PubMed]

K. J. Friston, “Bayesian estimation of dynamical systems: an application to fMRI,” NeuroImage 16, 513–530 (2002).
[CrossRef] [PubMed]

A. M. Dale, B. Fischl, M. I. Sereno, “Cortical surface-based analysis. I. Segmentation and surface reconstruction,” NeuroImage 9, 179–194 (1999).
[CrossRef] [PubMed]

Neurosci. Lett. (1)

J. Steinbrink, M. Kohl, H. Obrig, G. Curio, F. Syre, F. Thomas, H. Wabnitz, H. Rinneberg, A. Villringer, “Somatosensory evoked fast optical intensity changes detected non-invasively in the adult human head,” Neurosci. Lett. 291, 105–108 (2000).
[CrossRef] [PubMed]

Opt. Eng. (1)

S. Fantini, M. A. Franceschini-Fantini, J. S. Maier, S. A. Walker, B. Barbieri, E. Gratton, “Frequency-domain multichannel optical detector for noninvasive tissue spectroscopy and oximetry,” Opt. Eng. 34, 32–42 (1995).
[CrossRef]

Opt. Exp. (5)

X. Cheng, D. A. Boas, “Systematic diffuse optical image errors resulting from uncertainty in the background optical properties,” Opt. Exp. 4, 299–307 (1999); http://www.opticsexpress.org .
[CrossRef]

S. R. Arridge, M. Schweiger, “A gradient-based optimisation scheme for optical tomography,” Opt. Exp. 2, 213–226 (1998); http://www.opticsexpress.org .
[CrossRef]

D. A. Boas, T. J. Gaudette, S. R. Arridge, “Simultaneous imaging and optode calibration with diffuse optical tomography,” Opt. Exp. 8, 263–270 (2001); http://www.opticsexpress.com .
[CrossRef]

V. Kolehmainen, M. Vauhkonen, J. P. Kaipio, S. R. Arridge, “Recovery of piecewise constant coefficients in optical diffusion tomography,” Opt. Exp. 7, 468–481 (2000); http://www.opticsexpress.org .
[CrossRef]

M. Kilmer, E. Miller, D. A. Boas, D. Brooks, “A shape-based reconstruction technique for DPDW data,” Opt. Exp. 7, 481–491 (2000); http://www.opticsexpress.com .
[CrossRef]

Opt. Lett. (2)

Pediatr. Res. (1)

S. R. Hintz, W.-F. Cheong, J. P. van Houten, D. K. Stevenson, D. A. Benaron, “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging,” Pediatr. Res. 45, 54–59 (1999).
[CrossRef] [PubMed]

Philos. Trans. R. Soc. London Ser. B (1)

B. Chance, D. T. Delpy, C. E. Cooper, E. O. R. Reynolds, eds., “Near-infrared spectroscopy and imaging of living systems,” Philos. Trans. R. Soc. London Ser. B 352, 649–763 (1997)

Phys. Med. Biol. (6)

A. Kienle, T. Glanzmann, “In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model,” Phys. Med. Biol. 44, 2689–2702 (1999).
[CrossRef] [PubMed]

S. R. Arridge, J. C. Hebden, “Optical imaging in medicine: II. Modelling and reconstruction,” Phys. Med. Biol. 42, 841–854 (1997).
[CrossRef] [PubMed]

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

A. Torricelli, A. Pifferi, P. Taroni, E. Giambattistelli, R. Cubeddu, “In vivo optical characterization of human tissues from 610 to 1010 nm by time-resolved reflectance spectroscopy,” Phys. Med. Biol. 46, 2227–2237 (2001).
[CrossRef] [PubMed]

S. R. Arridge, M. Hiraoka, M. Schweiger, “Statistical basis for the determination of optical pathlength in tissue,” Phys. Med. Biol. 40, 1539–1558 (1995).
[CrossRef] [PubMed]

A. H. Hielscher, R. E. Alcouffe, R. L. Barbour, “Comparison of finite-difference transport and diffusion calculations for photon migration in homogeneous and heterogeneous tissues,” Phys. Med. Biol. 43, 1285–1302 (1998).
[CrossRef] [PubMed]

Phys. Rev. Lett. (1)

K. M. Yoo, F. Liu, R. R. Alfano, “When does the diffusion approximation fail to describe photon transport in random media?,” Phys. Rev. Lett. 64, 2647–2650 (1990).
[CrossRef] [PubMed]

Proc. Natl. Acad. Sci. USA (2)

N. Shah, A. Cerussi, C. Eker, J. Espinoza, J. Butler, J. Fishkin, R. Hornung, B. Tromberg, “Noninvasive functional optical spectroscopy of human breast tissue,” Proc. Natl. Acad. Sci. USA 98, 4420–4425 (2001).
[CrossRef] [PubMed]

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

Radiology (1)

B. W. Pogue, T. O. McBride, S. Osterman, S. Poplack, U. Osterberg, K. D. Paulsen, “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: pilot results in the breast,” Radiology 218(1), 261–266 (2001).

Rev. Mod. Phys. (1)

M. Hämäläinen, R. Hari, R. Ilmoniemi, J. Knuutila, O. V. Lounasmaa, “Magnetoencephalography—theory, instrumentation, and applications to noninvasive studies of the working human brain,” Rev. Mod. Phys. 65, 413–497 (1993).
[CrossRef]

Rev. Sci. Instrum. (1)

F. E. Schmidt, M. E. Fry, E. M. C. Hillman, J. C. Hebden, D. T. Delpy, “A 32-channel time-resolved instrument for medical optical tomography,” Rev. Sci. Instrum. 71, 256–265 (2000).
[CrossRef]

Trends Neurosci. (1)

A. Villringer, B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function,” Trends Neurosci. 20, 435–442 (1997).
[CrossRef] [PubMed]

Other (22)

D. A. Boas, M. A. Franceschini, A. K. Dunn, G. Strangman, “Noninvasive imaging of cerebral activation with diffuse optical tomography,” in In Vivo Optical Imaging of Brain Function, R. D. Frostig, ed. (CRC Press, Boca Raton, Fla., 2002), pp. 193–221.

A. Klose, A. H. Hielscher, K. M. Hanson, J. Beuthan, “Three-dimensional optical tomography of a finger joint model for diagnostic of rheumatoid arthritis,” in Photon Propagation in Tissue IV, D. A. Benaron, B. Chance, M. Ferrari, M. Kohl, eds., Proc. SPIE3566, 151–160 (1998).
[CrossRef]

R. Barbour, H. Graber, Y. Wang, J. Chang, R. Aronson, “A perturbation approach for optical diffusion tomography using continuous-wave and time-resolved data,” in Medical Optical Tomography: Functional Imaging and Monitoring, Vol. IS 11 of the SPIE Institute Series (SPIE, Bellingham, Wash., 1993),pp. 87–120.

S. R. Arridge, M. Schweiger, “Reconstruction in optical tomography using MRI based prior knowledge,” in Information Processing in Medical Imaging, Y. Bizais, C. Barillot, R. di Paola, eds. (Kluwer, Dordrecht, The Netherlands, 1995), pp. 77–88.

K. M. Hanson, G. S. Cunningham, S. S. Saquib, “Inversion based on computational simulations,” in Maximum Entropy and Bayesian Methods, G. J. Erickson, J. T. Rychert, C. R. Smith, eds. (Kluwer Academic, Dordrecht, The Netherlands, 1998), pp. 121–135.
[CrossRef]

S. S. Saquib, K. M. Hanson, G. S. Cunningham, “Model-based image reconstruction from time-resolved diffusion data,” in Medical Imaging 1997: Image Processing, K. M. Hanson, ed., Proc. SPIE3034, 369–380 (1997).
[CrossRef]

G. Nicholls, C. Fox, “Prior modelling and posterior sampling in impedance imaging,” in Bayesian Inference for Inverse Problems, A. Mohammad-Djafari, ed., Proc. SPIE3459, 116–127 (1998).
[CrossRef]

J. C. Tamraz, Y. G. Comair, Atlas of Regional Anatomy of the Brain Using MRI: With Functional Correlations (Springer, New York, 2000).

A. Ishimaru, Wave Propagation and Scattering in Random Media (Academic, New York, 1978), Vol. 1.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in C: The Art of Scientific Computing (Cambridge U. Press, 1992); available at http://lib-www.lanl.gov/numerical/bookcpdf.html. .

S. J. Press, Applied Multivariate Analysis: Using Bayesian and Frequentist Methods of Interference, 2nd ed. (Krieger, Malabar, Fla., 1982).

R. D. Richtmeyer, K. W. Morton, Difference Methods for Initial-Value Problems (Wiley, New York, 1967).

J. W. Thomas, Numerical Partial Differential Equations: Finite Difference Methods (Springer-Verlag, New York, 1995).

J. D. Oakley, “Magnetic resonance imaging based correction and reconstruction of positron emission tomography images,” Ph.D. dissertation (Service Hospitalier Frederic Joliot, CEA, Orsay, France, 2000).

I. Kwee, “Towards a Bayesian framework for optical tomography,” Ph.D. dissertation (Department of Medical Physics and Bioengineering, University College London, London, 1999).

D. J. C. MacKay, “Information theory, inference, and learning algorithms,” Chap. 3, available at http://www.inference.phy.cam.ac.uk/mackay/book.html .

J. Berger, Statistical Decision Theory and Bayesian Analysis (Springer, New York, 1985).
[CrossRef]

S. J. Press, Bayesian Statistics: Principles, Models, and Applications, Wiley Series in Probability and Statistics (Wiley, New York, 1989).

D. S. Sivia, Data Analysis: A Bayesian Tutorial (Oxford U. Press, Oxford, U.K., 1996).

S. F. Gull, “Bayesian inductive inference and maximum entropy,” in Foundations, Vol. 1 of Maximum Entropy and Bayesian Methods in Science and Engineering, G. R. Erickson, C. R. Smith, eds. (Kluwer, Dordrecht, The Netherlands, 1988).
[CrossRef]

R. M. Neal, “Probabilistic inference using Markov chain Monte Carlo methods,” Tech. Rep. CRG-TR-93-1 (Department of Computer Science, University of Toronto, Toronto, 1993); available at http://www.cs.toronto.edu/∼radford/review.abstract.html .

Note that for us this acronym does not imply association with hyperbolic equations. We are evolving a parabolic equation.

Cited By

OSA participates in CrossRef's Cited-By Linking service. Citing articles from OSA journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (10)

Fig. 1
Fig. 1

Illustration of Bayesian inference of unknown parameters x given the measured signal vector y. The complete model comprises a forward model f(x) (dotted curve) and an inference noise model, giving the joint PDF p(y, x) that can be written as a prior p(x) multiplied by a likelihood p(y|x). The inference noise model describes all measurement and model errors; here we use independent Gaussian noise with signal-dependent width σ(f).

Fig. 2
Fig. 2

Simulated optode arrangement and placement on the head (the face, pointing downward, is mostly hidden). 3-D MR-segmented head geometry is exposed by a sagittal slice. The tissue-type color coding on this slice is, from lightest to darkest, scalp, skull, CSF, brain.

Fig. 3
Fig. 3

Signals and noise models. (a) Typical signal expectation vector f ≡ {f m } for m = 1 … M, corresponding to N p = 1.1 × 106 detected photons, with error bars representing the noise standard deviation σ used for inference. The eight time courses correspond to the interval 0.2–2.0 ns and are labeled according to source and detector number. The 1 photon level is shown by the dashed line; the level for crossover to fractional-error-dominated noise at 1/∊2 is shown by the dotted line for ∊ = 0.05. (b) The solid line is the inference noise σ(f) given in Eq. (6), and the dashed-dotted line is the simulated experimental noise σsim(f) given in Eq. (7), plotted horizontally to share the same vertical scale as (a). (c) A simulated noisy signal vector y generated by the addition of Gaussian noise of size σsim(f) to the expectation f on same horizontal axis as (a). (d) The residual β m [in standard deviation units, see Eq. A(3)] that would result from the y and f shown on same horizontal axis as (a).

Fig. 4
Fig. 4

Tracking of inferred optical parameters of a homogeneous head model by use of noisy signals derived from the same model. (a) and (b) The effect that a change in the true absorption μa,hom0 has on inferred μ a,hom and μ s,hom′, respectively. The range of total detected photons N p is from 3.4 × 106 at the smallest μa,hom0 to 3.6 × 105 at the largest. (c) and (d) Same as (a) and (b) except for a change of the true reduced scattering μs,hom0 over which N p varies from 1.8 × 106 to 3.5 × 105. The error bars show ±1σ about the MAP (best-guess) value for the (marginal) posterior distribution of inferred values, computed by the methods of Appendix A. For comparison, the thin lines show the true values. The fractional model error is ∊ = 0.05.

Fig. 5
Fig. 5

Same as Fig. 4, except the noisy signals are generated by use of the segmented forward model, sweeping over a range of brain parameters. (The scalp and skull are fixed at the standard parameters given in Table 1.) The inference is still performed by the homogeneous model. The dashed lines show true parameters volume averaged over a depth of 17 mm. (We chose a constant effective thickness of 4 mm for the brain’s volume contribution, a typical time-independent fluence decay length in a semi-infinite brain.) N p spans 2.4 × 106 to 2.1 × 106 over the range of μa,brain0 and 2.1 × 106 to 2.2 × 106 over the range of μs,brain0. The fractional model error is still ∊ = 0.05.

Fig. 6
Fig. 6

Tracking of inferred brain optical parameters in a segmented model by use of noisy signals also derived from the segmented model. (The scalp and skull are fixed at the standard parameters given in Table 1, and the inferred scalp and skull parameters are not shown.) N p and ∊ are the same as for Fig. 5.

Fig. 7
Fig. 7

Expected percentage marginal error as a function of noise model N p (total detected photons) and ∊ (fractional model error) for parameters (a) μ a,brain and (b) μ s,brain′. The standard set of optical properties are used for inference with ℋseg and simulated noisy signals from the same model. Note that the contour lines bend quite sharply at the transition from Poisson-statistics-limited error (lower left) to model-limited error (upper right).

Fig. 8
Fig. 8

Views of the posterior distribution p(x|y, ℋseg) with signals y from the same forward model (2-mm lattice) by use of our standard optical parameters given in Table 1. Only 3.2 × 105 photons were collected, and ∊ = 0.1. The three columns of graphs show the μ a s ′ plane separately for each tissue type. (a), (b), and (c) show true x 0 (dot), x MAP (cross), and the marginal PDF as an elliptical contour enclosing 63% of the probability mass in the Gaussian posterior approximation. The contour is at e -1 times the peak density. (d), (e), and (f) show for comparison, on the same axes, conditional distributions (slices through the PDF with other components of x fixed at the x MAP values) at contours of e -1 (shown with thicker line), e -3, e -10, e -30, e -100, e -300, and e -1000 times the peak density. (g), (h), and (i) show 123 independent samples from the posterior obtained by MCMC. This displays the true marginal posterior PDF as a density cloud.

Fig. 9
Fig. 9

(a) Approximate error of the 2-mm lattice forward model signal expectation, expressed as a ratio against its (more accurate) 1-mm lattice equivalent. The standard set of optical properties is used for the segmented head model. (b) The normalized residual β m , which results when we compare the 1-mm lattice signal with the 2-mm lattice signal using noise model parameters y p = 10-4 and ∊ = 0.2.

Fig. 10
Fig. 10

Inference by use of the 2-mm lattice forward model ℋseg on simulated noisy signals generated from a 1-mm lattice forward model. The detection time was larger than in Fig. 6, with N p spanning 1.18 × 107 to 1.35 × 107 over the range of μa,brain0 and μs,brain0. The fractional model error of ∊ = 0.2 was chosen to reflect our knowledge of the 2-mm lattice model errors.

Tables (1)

Tables Icon

Table 1 Standard Set of Optical Properties of Human Head Tissue Types Used in this Studya

Equations (19)

Equations on this page are rendered with MathJax. Learn more.

px|y,   py|x, px|,
py|x  exp-Ly; x,
Ly; x=12m=1Mln σm2+12m=1Mfmx-ym2σm2.
px|y  exp-Ly; xxnxn,min, xn,maxn0otherwise,
1νt ϕ=·κϕ-μaϕ+q,
σf=1,f1f1/2,1<f1/2f,f>1/2.
σsimf=1,f1f1/2,f>1.
ym=maxfmx0+nm, 0, m=1M,
Npm=1M ym
xi+1=xi-H-1xi·Lxi,
Lxn=m=1MJmnσmβm+1-βm2σm,
βmfmx-ymσm,
Jmnx1δxfmx+δxen-fmx,
HHapproxJ¯TJ¯,
J¯mnβmxn=Jmnσm1-βmσm
MAP=Happrox-1.
aaababTbb.
a-1=aa-abbb-1abT.
x κ ϕxri,j,kκi+12,j,kϕi+1,j,k-ϕi,j,k-κi-12,j,kϕi,j,k-ϕi-1,j,kΔx2,

Metrics