Near Infrared Spectroscopic Imaging: Translation to Clinic

  • Brian Pogue
  • Shudong Jiang
  • Hamid Dehghani
  • Keith D. Paulsen
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 778)

Keywords

Turbid Medium Diffuse Optical Tomography Scattering Power Tissue Phantom Chromophore Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J. G. Webster, ed., The Design of Pulse Oximeters, Medical Science Series (Philadelphia: Institute of Physics Publishers, 1997).Google Scholar
  2. [2]
    O. Jarlman et al., “Relation between lightscanning and the histologic and mammo-graphic appearance of malignant breast tumors.” Acta Radiol., Vol. 33, 1992, pp. 63–68.Google Scholar
  3. [3]
    M. Cutler, “Transillumination as an aid in the diagnosis of breast lesions.” Surg. Gyn. Obst., Vol. 48, 1929, pp. 721–729.Google Scholar
  4. [4]
    C. H. Cartwright, “Infra-red transmission of the flesh.” J. Opt. Soc. Am., Vol. 20, 1930, pp. 81–84.Google Scholar
  5. [5]
    D. J. Watmough, “Transillumination of breast tissues: factors governing optimal imaging of lesions.” Radiol., Vol. 147, 1982, pp. 89–92.Google Scholar
  6. [6]
    R. J. Bartrum and H. C. Crow, “Transillumination light scanning to diagnose breast cancer: a feasibility study.” Am. J. Roentg., Vol. 142, 1984, pp. 409–414.Google Scholar
  7. [7]
    G. A. Navarro and A. E. Profio, “Contrast in diaphanography of the breast.” Med. Phys., Vol. 15, 1988, pp. 181–187.CrossRefGoogle Scholar
  8. [8]
    A. Alveryd et al., “Lightscanning versus mammography for the detection of breast cancer in screening and clinical practice. A Swedish multicenter study.” Cancer: Diag. Treat. Res., Vol. 65(8), 1990, pp. 1671–1677.Google Scholar
  9. [9]
    F. F. Jobsis, “Non-invasive, infra-red monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters.” Science, Vol. 198, 1977, pp. 1264–1267Google Scholar
  10. [10]
    P. M. Middleton and J. A. Henry, “Pulse oximetry: evolution and directions.” International Journal of Clinical Practice, Vol. 54(7), 2000, pp. 438–444.Google Scholar
  11. [11]
    J. W. Severinghaus, “History and recent developments in pulse oximetry.” Scandinavian Journal of Clinical & Laboratory Investigation—Supplement, Vol. 214, 1993, pp. 105–111.Google Scholar
  12. [12]
    Y. Mendelson, “Pulse oximetry: Theory and applications for noninvasive monitoring.” Clinical Chemistry, Vol. 38(9), 1992, pp. 1601–1607.Google Scholar
  13. [13]
    W. A. Bowes et al., “Pulse oximetry: a review of the theory, accuracy, and clinical applications.” Obstetrics & Gynecology, Vol. 74(3, Pt. 2), 1989, pp. 541–546.Google Scholar
  14. [14]
    M. Tamura et al., “The simultaneous measurements of tissue oxygen concentration and energy state by near-infrared and nuclear magnetic resonance spectroscopy.” Advances in Experimental Medicine & Biology, Vol. 222, 1988, pp. 359–63.1988.Google Scholar
  15. [15]
    S. Wray et al., “Characterization of the near infrared absorption spectra of cytochrome aa3 and haemoglobin for the non-invasive monitoring of cerebral oxygenation.” Bio-chem. Biophys. Acta, Vol. 933, 1988, pp. 184–192.Google Scholar
  16. [16]
    H. Miyake et al., “The detection of cytochrome oxidase heme iron and copper absorption in the blood-perfused and blood-free brain in normoxia and hypoxia.” Analytical Biochemistry, Vol. 192(1), 1991, pp. 149–155.CrossRefGoogle Scholar
  17. [17]
    H. R. Heekeren et al., “Noninvasive assessment of changes in cytochrome-c oxidase oxidation in human subjects during visual stimulation.” Journal of Cerebral Blood Flow & Metabolism, Vol. 19(6), 1999, pp. 592–603.Google Scholar
  18. [18]
    W. Bank and B. Chance, “Diagnosis of defects in oxidative muscle metabolism by non-invasive tissue oximetry.” Molecular & Cellular Biochemistry, Vol. 174(1-2), 1997, pp. 7–10.Google Scholar
  19. [19]
    A. Villringer and B. Chance, “Non-invasive optical spectroscopy and imaging of human brain function.” Trends in Neurosciences, Vol. 20(10), 1997, pp. 435–442.CrossRefGoogle Scholar
  20. [20]
    A. E. Cerussi et al., “Sources of absorption and scattering contrast for near-infrared optical mammography.” Academic Radiology, Vol. 8(3), 2001, pp. 211–218.CrossRefGoogle Scholar
  21. [21]
    A. H. Hielscher, J. R. Mourant, and I. J. Bigio, “Influence of particle size and concentration on the diffuse backscattering of polarized light from tissue phantoms and biological cell suspensions.” Appl. Opt., Vol. 36(1), 1997, pp. 125–135.Google Scholar
  22. [22]
    J. R. Mourant et al., “Mechanisms of light scattering from biological cells relevant to noninvasive optical tissue diagnostics.” Appl. Opt., Vol. 37(16), 1998, pp. 3586–3593.Google Scholar
  23. [23]
    J. R. Mourant, T. M. Johnson, and J. P. Freyer, “Characterizing mammalian cells and cell phantoms by polarized backscattering fiberoptic measurements.” Appl. Opt., Vol. 40(28), 2001, pp. 5114–5123.Google Scholar
  24. [24]
    V. Backman et al., “Detection of preinvasive cancer cells.” Nature, Vol. 406(6791), 2000, pp. 35–36.Google Scholar
  25. [25]
    R. S. Gurjar et al., “Imaging human epithelial properties with polarized light-scattering spectroscopy.” Nature Medicine, Vol. 7(11), 2001, pp. 1245–1248.CrossRefGoogle Scholar
  26. [26]
    A. Wax et al., “Determination of particle size by using the angular distribution of backscattered light as measured with low-coherence interferometry.” Journal of the Optical Society of America, A: Optics, Image Science, & Vision, Vol. 19(4), 2002, pp. 737–744.Google Scholar
  27. [27]
    W. M. Star, J. P. A Marijnissen, and M. J. C. van Gemert, “Light dosimetry in optical phantoms and in tissues: I. Multiple flux and transport theory.” Phys. Med. Biol., Vol. 33(4), 1988, pp. 437–454.CrossRefGoogle Scholar
  28. [28]
    M. S. Patterson, B. C. Wilson, and D. R. Wyman, “The propagation of optical radiation in tissue: I. Models of radiation transport and their application.” Lasers Med. Sci., Vol.6, 1990, pp. 155–168.Google Scholar
  29. [29]
    E. M. Gelbard, “Spherical harmonic methods,” in Computing Methods in Reactor Physics (New York: Gordon and Breach, 1964).Google Scholar
  30. [30]
    J. J. Duderstadt and L. J. Hamilton, Nuclear Reactor Analysis (New York: John Wiley and Sons, 1976), pp. 133–138.Google Scholar
  31. [31]
    M. S. Patterson and B. C. Wilson, “Time resolved reflectance and transmittance for the non-invasive measurement of tissue optical properties.” Appl. Opt., Vol. 28, 1989, pp. 2331–2336.Google Scholar
  32. [32]
    M. S. Patterson et al., “Frequency-domain reflectance for the determination of the scattering and absorption properties of tissue.” Appl. Opt., Vol. 30(24), 1991, pp. 4474_4476.Google Scholar
  33. [33]
    J. Fishkin et al., “Diffusion of intensity modulated near infrared light in turbid media.” Proc. SPIE, Vol. 1431, 1991, pp. 122–135.Google Scholar
  34. [34]
    J. B. Fishkin and E. Gratton, “Propagation of photon-density waves in strongly scattering media containing an absorbing semi-infinite plane bounded by a straight edge.” J. Opt. Soc. Am. A, Vol. 10(1), 1993, pp. 127–140.Google Scholar
  35. [35]
    J. B. Fishkin et al., “Gigahertz photon density waves in a turbid medium: Theory and experiments.” Phys. Rev. E, Vol. 53(3), 1996, pp. 2307–2319.CrossRefGoogle Scholar
  36. [36]
    T. J. Farrell, M. S. Patterson, and B. C. Wilson, “A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties.” Med. Phys., Vol. 19(4), 1992, pp. 879–888.CrossRefGoogle Scholar
  37. [37]
    A. Kienle and M. S. Patterson, “Determination of the optical properties of semi-infinite turbid media from frequency-domain reflectance close to the source.” Phys. Med. Biol., Vol. 42(9), 1997, pp. 1801–1819.CrossRefGoogle Scholar
  38. [38]
    A. Kienle and M. S. Patterson, “Improved solutions of the steady-state and the time-resolved diffusion equations for reflectance from a semi-infinite turbid medium.” J. Opt. Soc. Am. A—Optics & Image Science, Vol. 14(1), 1997, pp. 246–254.Google Scholar
  39. [39]
    A. Kienle and M. S. Patterson, “Determination of the optical properties of turbid media from a single Monte Carlo simulation.” Phys. Med. Biol., Vol. 41(10), 1996, pp. 2221–2227.CrossRefGoogle Scholar
  40. [40]
    S. J. Matcher and C. E. Cooper, “Absolute quantification of deoxyhaemoglobin concentration in tissue near infrared spectroscopy.” Phys. Med. Biol., Vol. 39, 1994, pp. 1295–1312.Google Scholar
  41. [41]
    C. E. Cooper et al., “The noninvasive measurement of absolute cerebral deoxyhaemoglobin concentration and mean optical pathlength in the neonatal brain by second derivative near infrared spectroscopy.” Pediat. Res., Vol. 39, 1996, pp. 32–38.Google Scholar
  42. [42]
    S. R. Arridge, M. Cope, and D. T. Delpy, “The theoretical basis for the determination of optical pathlengths in tissue: Temporal and frequency analysis.” Phys. Med. Biol., Vol. 37(7), 1992, pp. 1531–1560.CrossRefGoogle Scholar
  43. [43]
    B. W. Pogue and M. S. Patterson, “Frequency domain optical absorption spectroscopy of finite tissue volumes using diffusion theory.” Phys. Med. Biol., Vol. 39, 1994, pp. 1157–1180.CrossRefGoogle Scholar
  44. [44]
    J. R. Singer et al., “Image reconstruction of the interior of bodies that diffuse radiation.” Science, Vol. 248, 1990, pp. 990–993.Google Scholar
  45. [45]
    S. R. Arridge and M. Schweiger, “Image reconstruction in optical tomography.” Phil. Trans. R. Soc. Lond. B, Vol. 352,1997, pp. 717–726.Google Scholar
  46. [46]
    S. R. Arridge et al., “Reconstruction methods for infrared absorption imaging.” Proc. SPIE, Vol. 1431, 1991, pp. 204–215.Google Scholar
  47. [47]
    S. R. Arridge, M. Schweiger, and D. T. Delpy, “Iterative reconstruction of near infrared absorption images.” Proc. SPIE, Vol. 1767, 1992, pp. 372–383.Google Scholar
  48. [48]
    E. Gratton et al., “A novel approach to laser tomography.” Bioimaging, Vol. 1, 1993, pp. 40–46.CrossRefGoogle Scholar
  49. [49]
    S. Nioka et al., “Optical imaging of human breast cancer.” Advances in Experimental Medicine and Biology, Vol. 361, 1994, pp. 171–179.Google Scholar
  50. [50]
    M. A. O’Leary et al., “Experimental images of heterogeneous turbid media by frequency-domain diffusing-photon tomography.” Opt. Lett., Vol. 20(5), 1995, pp. 426–428.Google Scholar
  51. [51]
    D. A. Boas et al., “Detection and characterization of optical inhomogeneities with diffuse photon density waves: A signal-to-noise analysis.” Appl. Opt., Vol. 36, 1997, pp. 75–92.Google Scholar
  52. [52]
    D. Boas, “A fundamental limitation of linearized algorithms for diffuse optical tomography.” Opt. Express, Vol. 1(13), 1997, pp. 404–413.Google Scholar
  53. [53]
    W. Cai et al., “Time-resolved optical diffusion tomographic image reconstruction in highly scattering turbid media.” Proceedings of the National Academy of Sciences of the United States of America, Vol. 93(24), 1996, pp. 13561–13564.CrossRefGoogle Scholar
  54. [54]
    S. Walker, S. Fantini, and E. Gratton, “Image reconstruction by backprojection from frequency-domain optical measurements in highly scattering media.” Appl Opt., Vol. 36(1), 1997, pp. 170–179.CrossRefGoogle Scholar
  55. [55]
    S. R. Arridge and M. Schweiger, “Inverse methods for optical tomography,” in Information Processing in Medical Imaging, H. H. Barrett, ed. (Flagstaff, AZ: Springer-Verlag, 1993), pp. 259–277.Google Scholar
  56. [56]
    S. R. Arridge and M. Schweiger, “Sensitivity to prior knowledge in optical tomographic reconstruction.” Proc. SPIE, Vol. 2389, 1995, pp. 378–388.Google Scholar
  57. [57]
    S. R. Arridge, “Optical tomography in medical imaging.” Inverse Problems, Vol. 15(2), 1999, pp. R41–R93.CrossRefMathSciNetMATHGoogle Scholar
  58. [58]
    H. Jiang and K. D. Paulsen, “A finite element based higher-order diffusion approximation of light propagation in tissues.” Proc. SPIE: Optical Tomography, Photon Migration, and Spectroscopy of Tissue and Model Media, 1995.Google Scholar
  59. [59]
    H. B. Jiang et al., “Simultaneous reconstruction of optical-absorption and scattering maps in turbid media from near-infrared frequency-domain data.” Optics Letters, Vol. 20(20), 1995, pp. 2128–2130.CrossRefGoogle Scholar
  60. [60]
    B. W. Pogue et al., “Initial assessment of a simple system for frequency domain diffuse optical tomography.” Phys. Med. Biol., Vol. 40, 1995, pp. 1709–1729.CrossRefGoogle Scholar
  61. [61]
    K. D. Paulsen and H. Jiang, “Spatially varying optical property reconstruction using a finite element diffusion equation approximation.” Med. Phys., Vol. 22(6), 1995, pp. 691–701.CrossRefGoogle Scholar
  62. [62]
    A. H. Hielscher, A. Klose, and K. M. Hanson, “Gradient-based iterative image reconstruction scheme for time-resolved optical tomography.” IEEE Trans. Med. Imaging, Vol. 18(3), 1999, pp. 262–271.CrossRefGoogle Scholar
  63. [63]
    S. B. Colak et al., “Tomographic image reconstruction from optical projections in light-diffusing media.” Appl. Opt., Vol. 36(1), 1997, pp. 180–213.Google Scholar
  64. [64]
    C. D. Kurth, J. M. Steven, and S. C. Nicolson, “Cerebral oxygenation during pediatric cardiac surgery using deep hypothermic circulatory arrest.” Anesthesiology, Vol. 82(1), 1995, pp. 74–82.Google Scholar
  65. [65]
    S. R. Hintz et al., “Bedside imaging of intracranial hemorrhage in the neonate using light: comparison with ultrasound, computed tomography, and magnetic resonance imaging.” Pediatric Research, Vol. 45(1), 1999, pp. 54–59.Google Scholar
  66. [66]
    E. M. Nemoto, H. Yonas, and A. Kassam, “Clinical experience with cerebral oximetry in stroke and cardiac arrest.” Critical Care Medicine, Vol. 28(4), 2000, pp. 1052–1054.Google Scholar
  67. [67]
    W. G. Chen et al., “Hemodynamic assessment of ischemic stroke with near-infrared spectroscopy.” Hangtian Yixue Yu Yixue Gongcheng/Space Medicine & Medical Engineering, Vol. 13(2), 2000, pp. 84–89.Google Scholar
  68. [68]
    Q. Zhang et al., “Study of near infrared technology for intracranial hematoma detection.” Journal of Biomedical Optics, Vol. 5(2), 2000, pp. 206–213.CrossRefGoogle Scholar
  69. [69]
    A. Kleinschmidt et al., “Simultaneous recording of cerebral blood oxygenation changes during human brain activation by magnetic resonance imaging and near-infrared spectroscopy.” J. Cereb. Blood Flow Met., Vol. 16, 1996, pp. 817–826.Google Scholar
  70. [70]
    H. Obrig et al., “Near-infrared spectroscopy: does it function in functional activation studies of the adult brain?” International Journal of Psychophysiology, Vol. 35(2-3), 2000, pp. 125–142.CrossRefGoogle Scholar
  71. [71]
    B. M. Mackert et al., “Non-invasive single-trial monitoring of human movement-related brain activation based on DC-magnetoencephalography.” NeuroReport, Vol. 12(8), 2001, pp. 1689–1692.Google Scholar
  72. [72]
    C. E. Elwell et al., “Oscillations in cerebral haemodynamics. Implications for functional activation studies.” Advances in Experimental Medicine & Biology, Vol. 471, 1999, pp. 57–65.Google Scholar
  73. [73]
    B. Chance, “Near-infrared (NIS) optical spectroscopy characterizes breast tissue hormonal and age status.” Academic Radiology, Vol. 8(3), 2001, pp. 209–210.CrossRefGoogle Scholar
  74. [74]
    B. J. Tromberg et al., “Non-invasive measurements of breast tissue optical properties using frequency-domain photon migration.” Phil. Trans. R. Soc. Lond. B, Vol. 352, 1997, pp. 661–668.CrossRefGoogle Scholar
  75. [75]
    N. Shah et al., “Noninvasive functional optical spectroscopy of human breast tissue.” Proceedings of the National Academy of Sciences of the United States of America, Vol. 98(8), 2001, pp. 4420–4425.CrossRefGoogle Scholar
  76. [76]
    S. Fantini et al., “Frequency-domain optical mammography: Edge effect corrections.” Med. Phys., Vol. 23, 1996, pp. 149–157.CrossRefGoogle Scholar
  77. [77]
    H. Jess et al., “Intensity modulated breast imaging: Technology and clinical pilot study results.” In Proceedings of the Advances in Optical Imaging and Photon Migration, Opt. Soc. Am., 1996.Google Scholar
  78. [78]
    M. A. Franceschini et al., “Frequency-domain techniques enhance optical mammography: initial clinical results.” Proc. Nat. Acad. Sci USA, Vol. 94(12), 1997, pp. 6468–6473.CrossRefGoogle Scholar
  79. [79]
    E. L. Heffer and S. Fantini, “Quantitative oximetry of breast tumors: a near-infrared method that identifies two optimal wavelengths for each tumor.” Appl. Opt., Vol. 41(19), 2002, pp. 3827–3839.Google Scholar
  80. [80]
    K. Suzuki et al., “Quantitative measurement of optical parameters in normal breasts using time-resolved spectroscopy: In vivo results of 30 Japanese women.” J. Biomed. Opt., Vol. 1(3), 1996, pp. 330–334.MATHGoogle Scholar
  81. [81]
    R. Cubeddu et al., “Effects of the menstrual cycle on the red and near-infrared optical properties of the human breast.” Photochemistry & Photobiology, Vol. 72(3), 2000, pp. 383–391.CrossRefGoogle Scholar
  82. [82]
    V. Quaresima, S. J. Matcher, and M. Ferrari, “Identification and quantification of intrinsic optical contrast for near-infrared mammography.” Photochem. Photobiol., Vol. 67, 1998, pp. 4–14.CrossRefGoogle Scholar
  83. [83]
    S. Fantini et al., “Performance of N-Images and spectral features in frequency-domain optical mammography.” In SPIE Technical Abstract Digest (SPIE Press, 1999).Google Scholar
  84. [84]
    T. J. Brukilacchio et al., “Instrumentation for imaging of breast lesions based on co-registered diffuse optical and x-ray tomography.” OSA Biomed. Top. Meetings, Technical Digest, Vol. SuE2, 2002, pp. 178–180.Google Scholar
  85. [85]
    J. Hoogenraad et al., “First results of the Phillips optical mammoscope.” Proc. SPIE, Vol. 3194, 1997.Google Scholar
  86. [86]
    R. J. Grable et al., “Optical computed tomography for imaging the breast: First look.” Proc. SPIE, Vol. 4082, 2000.Google Scholar
  87. [87]
    R. J. Grable, N. A. Gkanatsios, and S. L. Ponder, “Optical mammography.” Appl. Ra-diol., Vol. 29, 2000, pp. 18–20.Google Scholar
  88. [88]
    P. C. Jackson et al., “The development of a system for transillumination computed tomography.” Brit. J. Radiol., Vol. 60, 1987, pp. 375–380.Google Scholar
  89. [89]
    H. B. Jiang, “Optical image reconstruction based on the third-order diffusion equations.” Optics Express, Vol. 4(8), 1999, pp. 241–246.Google Scholar
  90. [90]
    Y. Xu et al., “Three-dimensional diffuse optical tomography of bones and joints.” J. Biomed. Opt., Vol. 7(1), 2002, pp. 88–92.CrossRefGoogle Scholar
  91. [91]
    R. L. Barbour et al., “A perturbation approach for optical diffusion tomography using continuous-wave and time resolved data.” In Medical Optical Tomography: Functional Imaging and Monitoring, G. Muller, ed. (Bellingham,WA: SPIE Publishers, 1993), pp. 87–120.Google Scholar
  92. [92]
    H. L. Graber, R. Aronson, and R. L. Barbour, “Nonlinear effects of localized absorption perturbations on the light distribution in a turbid medium.” J. Opt. Soc. Am. A, Optics Image Science and Vision, Vol. 15(4), 1998, pp. 834–848.Google Scholar
  93. [93]
    C. H. Schmitz et al., “Instrumentation for fast functional optical tomography.” Rev. Sci. Instr., Vol. 73(2), 2002, pp. 429–439.CrossRefMathSciNetGoogle Scholar
  94. [94]
    W. Zhu et al., “Iterative total least-squares image reconstruction algorithm for optical tomography by the conjugate gradient method.” J. Opt. Soc. Am. A, Vol. 14(4), 1997, pp. 799–807.Google Scholar
  95. [95]
    W. W. Zhu et al., “A wavelet-based multiresolution regularized least squares reconstruction approach for optical tomography.” IEEE Trans. Med. Imag., Vol. 16(2), 1997, pp. 210–217.Google Scholar
  96. [96]
    B. W. Pogue et al., “Comparison of imaging geometries for diffuse optical tomography of tissue.” Opt. Exp., Vol. 4(8), 1999, pp. 270–286, 1999.Google Scholar
  97. [97]
    H. Jiang et al., “Optical image reconstruction using frequency-domain data: simulations and experiments.” J. Opt. Soc. Am. A, Vol. 13(2), 1996, pp. 253–266.CrossRefGoogle Scholar
  98. [98]
    H. B. Jiang et al., “Frequency-domain optical image reconstruction in turbid media: An experimental study of single-target detectability.” Applied Optics, Vol. 36(1), 1997, pp. 52–63.Google Scholar
  99. [99]
    H. B. Jiang, “Frequency-domain fluorescent diffusion tomography: a finite-element-based algorithm and simulations.” Applied Optics, Vol. 37(22), 1998, pp. 5337–5343.CrossRefGoogle Scholar
  100. [100]
    H. B. Jiang, et al., “Improved continuous light diffusion imaging in single-and multi-target tissue-like phantoms.” Phys. Med. Biol., Vol. 43(3), 1998, pp. 675–693.CrossRefGoogle Scholar
  101. [101]
    H. B. Jiang et al., “Frequency-domain near-infrared photo diffusion imaging: Initial evaluation in multitarget tissuelike phantoms.” Med. Phys., Vol. 25(2), 1998, pp. 183–193.CrossRefGoogle Scholar
  102. [102]
    B. W. Pogue et al., “Instrumentation and design of a frequency-domain diffuse optical tomography imager for breast cancer detection.” Opt. Express, Vol. 1(13) 1997, pp. 391–403.CrossRefGoogle Scholar
  103. [103]
    B. W. Pogue et al., “Quantitative hemoglobin tomography with diffuse near-infrared spectroscopy: Pilot results in the breast.” Radiology, Vol. 218(1), 2001, pp. 261–266.Google Scholar
  104. [104]
    T. O. McBride et al., “Development and calibration of a parallel modulated near-infrared tomography system for hemoglobin imaging in vivo.” Rev. Sci. Instr., Vol. 72(3), 2001, pp. 1817–1824.CrossRefGoogle Scholar
  105. [105]
    T. O. McBride et al., “Multi-spectral near-infrared tomography: A case study in compensating for water and lipid content in hemoglobin imaging of the breast.” J. Biomed. Opt., Vol. 7(1), 2001, pp. 72–79.MathSciNetGoogle Scholar
  106. [106]
    T. O. McBride et al., “Near-infrared tomographic imaging of heterogeneous media: A preliminary study in excised breast tissue.” Proc. SPIE, Vol. 4250, 2001.Google Scholar
  107. [107]
    M. Firbank, M. Oda, and D. T. Delpy, “An improved design for a stable and reproducible phantom material for use in near-infrared spectroscopy and imaging.” Phys. Med. Biol., Vol. 40, 1995, pp. 955–961.CrossRefGoogle Scholar
  108. [108]
    B. J. Tromberg et al., “Non-invasive in vivo characterization of breast tumors using photon migration spectroscopy.” Neoplasia, Vol. 2(1-2), 2000, 26–40.Google Scholar
  109. [109]
    S. Srinivasan et al., “Interpreting hemoglobin and water concentration, oxygen saturation, and scattering measured by near-infrared tomography of normal breast in vivo.” Proceedings of the National Academy of Sciences of the United States of America, Vol. 100(21), 2003, pp. 12349–12354.CrossRefGoogle Scholar
  110. [110]
    B. W. Pogue et al., “Characterization of hemoglobin, qater and NIR scattering in breast tissue: Analysis of inter-subject variability and menstrual cycle changes.” J. Biomed. Opt., Vol. 9(3), 2004, pp. 541–552.CrossRefGoogle Scholar
  111. [111]
    H. Vorherr, “Fibrocystic breast disease: pathophysiology, pathomorphology, clinical picture, and management.” American Journal of Obstetrics & Gynecology, Vol. 154(1), 1986, pp. 161–179.Google Scholar
  112. [112]
    S. J. Graham et al., “Quantitative correlation of breast tissue parameters using magnetic resonance and X-ray mammography.” British Journal of Cancer, Vol. 73(2), 1996, pp. 162–168.Google Scholar
  113. [113]
    C. S. Poon et al., “Quantitative magnetic resonance imaging parameters and their relationship to mammographic pattern.” Journal of the National Cancer Institute, Vol. 84(10), 1992, pp. 777–781.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • Brian Pogue
    • 1
  • Shudong Jiang
    • 2
  • Hamid Dehghani
    • 1
  • Keith D. Paulsen
    • 1
  1. 1.Thayer School of EngineeringDartmouth CollegeUSA
  2. 2.Tokyo Institute of TechnologyTokyoJapan

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