Alternative Breast Imaging pp 201-226 | Cite as
Near Infrared Spectroscopic Imaging: Translation to Clinic
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Keywords
Turbid Medium Diffuse Optical Tomography Scattering Power Tissue Phantom Chromophore Concentration
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References
- [1]J. G. Webster, ed., The Design of Pulse Oximeters, Medical Science Series (Philadelphia: Institute of Physics Publishers, 1997).Google Scholar
- [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]M. Cutler, “Transillumination as an aid in the diagnosis of breast lesions.” Surg. Gyn. Obst., Vol. 48, 1929, pp. 721–729.Google Scholar
- [4]C. H. Cartwright, “Infra-red transmission of the flesh.” J. Opt. Soc. Am., Vol. 20, 1930, pp. 81–84.Google Scholar
- [5]D. J. Watmough, “Transillumination of breast tissues: factors governing optimal imaging of lesions.” Radiol., Vol. 147, 1982, pp. 89–92.Google Scholar
- [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]G. A. Navarro and A. E. Profio, “Contrast in diaphanography of the breast.” Med. Phys., Vol. 15, 1988, pp. 181–187.CrossRefGoogle Scholar
- [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]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]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]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]Y. Mendelson, “Pulse oximetry: Theory and applications for noninvasive monitoring.” Clinical Chemistry, Vol. 38(9), 1992, pp. 1601–1607.Google Scholar
- [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]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]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]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]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]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]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]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]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]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]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]V. Backman et al., “Detection of preinvasive cancer cells.” Nature, Vol. 406(6791), 2000, pp. 35–36.Google Scholar
- [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]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]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]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]E. M. Gelbard, “Spherical harmonic methods,” in Computing Methods in Reactor Physics (New York: Gordon and Breach, 1964).Google Scholar
- [30]J. J. Duderstadt and L. J. Hamilton, Nuclear Reactor Analysis (New York: John Wiley and Sons, 1976), pp. 133–138.Google Scholar
- [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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]S. R. Arridge et al., “Reconstruction methods for infrared absorption imaging.” Proc. SPIE, Vol. 1431, 1991, pp. 204–215.Google Scholar
- [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]E. Gratton et al., “A novel approach to laser tomography.” Bioimaging, Vol. 1, 1993, pp. 40–46.CrossRefGoogle Scholar
- [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]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]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]D. Boas, “A fundamental limitation of linearized algorithms for diffuse optical tomography.” Opt. Express, Vol. 1(13), 1997, pp. 404–413.Google Scholar
- [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]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]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]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]S. R. Arridge, “Optical tomography in medical imaging.” Inverse Problems, Vol. 15(2), 1999, pp. R41–R93.CrossRefMathSciNetMATHGoogle Scholar
- [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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]S. Fantini et al., “Frequency-domain optical mammography: Edge effect corrections.” Med. Phys., Vol. 23, 1996, pp. 149–157.CrossRefGoogle Scholar
- [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]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]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]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]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]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]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]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]J. Hoogenraad et al., “First results of the Phillips optical mammoscope.” Proc. SPIE, Vol. 3194, 1997.Google Scholar
- [86]R. J. Grable et al., “Optical computed tomography for imaging the breast: First look.” Proc. SPIE, Vol. 4082, 2000.Google Scholar
- [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]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]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]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]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]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]C. H. Schmitz et al., “Instrumentation for fast functional optical tomography.” Rev. Sci. Instr., Vol. 73(2), 2002, pp. 429–439.CrossRefMathSciNetGoogle Scholar
- [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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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]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
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