Abstract

A two-layer Monte Carlo lookup table-based inverse model is validated with two-layered phantoms across physiologically relevant optical property ranges. Reflectance data for source-detector separations of 370 μm and 740 μm were collected from these two-layered phantoms and top layer thickness, reduced scattering coefficient and the top and bottom layer absorption coefficients were extracted using the inverse model and compared to the known values. The results of the phantom verification show that this method is able to accurately extract top layer thickness and scattering when the top layer thickness ranges from 0 to 550 μm. In this range, top layer thicknesses were measured with an average error of 10% and the reduced scattering coefficient was measured with an average error of 15%. The accuracy of top and bottom layer absorption coefficient measurements was found to be highly dependent on top layer thickness, which agrees with physical expectation; however, within appropriate thickness ranges, the error for absorption properties varies from 12–25%.

© 2013 Optical Society of America

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    [CrossRef]

2013 (1)

R. Hennessy, S. L. Lim, M. K. Markey, and J. W. Tunnell, “Monte Carlo lookup table-based inverse model for extracting optical properties from tissue-simulating phantoms using diffuse reflectance spectroscopy,” J. Biomed. Opt.18(3), 37003 (2013).
[CrossRef]

2012 (1)

B. Nichols, N. Rajaram, and J. W. Tunnell, “Performance of a lookup table-based approach for measuring tissue optical properties with diffuse optical spectroscopy,” J. Biomed. Opt.17(5), 057001 (2012).
[CrossRef] [PubMed]

2011 (1)

2010 (4)

G. Zonios and A. Dimou, “Simple two-layer reflectance model for biological tissue applications: lower absorbing layer,” Appl. Opt.49(27), 5026–5031 (2010).
[CrossRef] [PubMed]

D. Yudovsky and L. Pilon, “Rapid and accurate estimation of blood saturation, melanin content, and epidermis thickness from spectral diffuse reflectance,” Appl. Opt.49(10), 1707–1719 (2010).
[CrossRef] [PubMed]

G. Zonios, A. Dimou, M. Carrara, and R. Marchesini, “In vivo optical properties of melanocytic skin lesions: common nevi, dysplastic nevi and malignant melanoma,” Photochem. Photobiol.86(1) 236–240 (2010).
[CrossRef]

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

2009 (1)

2008 (4)

E. Borisova, P. Troyanova, P. Pavlova, and L. Avramov, “Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy,” Quantum Electronics, 38(6), 597 (2008).
[CrossRef]

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt.13(6), 060504 (2008).
[CrossRef]

G. Zonios, I. Bassukas, and A. Dimou, “Comparative evaluation of two simple diffuse reflectance models for biological tissue applications,” Appl. Opt.47(27), 4965–4973 (2008).
[CrossRef] [PubMed]

N. Rajaram, T. H. Nguyen, and J. W. Tunnell, “Lookup table-based inverse model for determining optical properties of turbid media,” J. Biomed. Opt.13(5), 050501 (2008).
[CrossRef] [PubMed]

2007 (3)

2006 (2)

Q. Liu and N. Ramanujam, “Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra,” Appl. Opt.45(19), 4476–4490 (2006).
[CrossRef] [PubMed]

G. M. Palmer and N. Ramanujam, “Monte Carlo-based inverse model for calculating tissue optical properties. Part I: Theory and validation on synthetic phantoms,” Appl. Opt.45(5), 1062–1071 (2006).
[CrossRef] [PubMed]

2005 (1)

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

2004 (1)

2002 (1)

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

2001 (1)

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol.117(6), 1452–1457 (2001).
[CrossRef]

1999 (1)

1998 (2)

1997 (1)

L. Wang, S. Jacques, and L. Zheng, “CONV - convolution for responses to a finite diameter photon beam incident on multi-layered tissues,” Comput. Meth. Prog. Bio.54(3), 141–150 (1997).
[CrossRef]

1996 (1)

1995 (2)

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio.47(2), 131–146 (1995).
[CrossRef]

F. Alizadeh, “Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization,” SIAM J. Optim.5(1), 13–51 (1995).
[CrossRef]

1993 (1)

1992 (2)

T. Farrell, M. Patterson, and B. Wilson, “A diffusion-theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys.19(4), 879–888 (1992).
[CrossRef] [PubMed]

T. J. Farrell, B. C. Wilson, and M. S. Patterson, “The use of a neural network to determine tissue optical properties from spatially resolved diffuse reflectance measurements,” Phys. Med. Biol.37(12), 2281–2286, (1992).
[CrossRef] [PubMed]

1981 (1)

S. Wan, R. R. Anderson, and J. A. Parrish, “Analytical modeling for the optical properties of the skin with in vitro and in vivo applications,” Photochem. Photobiol.34(4), 493–499 (1981).
[PubMed]

Aarnoudse, J. G.

Alerstam, E.

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt.13(6), 060504 (2008).
[CrossRef]

Alizadeh, F.

F. Alizadeh, “Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization,” SIAM J. Optim.5(1), 13–51 (1995).
[CrossRef]

Anderson, R. R.

S. Wan, R. R. Anderson, and J. A. Parrish, “Analytical modeling for the optical properties of the skin with in vitro and in vivo applications,” Photochem. Photobiol.34(4), 493–499 (1981).
[PubMed]

Andersson-Engels, S.

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt.13(6), 060504 (2008).
[CrossRef]

Atkinson, E. N.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Avramov, L.

E. Borisova, P. Troyanova, P. Pavlova, and L. Avramov, “Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy,” Quantum Electronics, 38(6), 597 (2008).
[CrossRef]

Backman, V.

Bassukas, I.

Bays, R.

Borisova, E.

E. Borisova, P. Troyanova, P. Pavlova, and L. Avramov, “Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy,” Quantum Electronics, 38(6), 597 (2008).
[CrossRef]

Brightwell, A.

Bykowski, J.

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol.117(6), 1452–1457 (2001).
[CrossRef]

Carnohan, M.

Carrara, M.

G. Zonios, A. Dimou, M. Carrara, and R. Marchesini, “In vivo optical properties of melanocytic skin lesions: common nevi, dysplastic nevi and malignant melanoma,” Photochem. Photobiol.86(1) 236–240 (2010).
[CrossRef]

Chang, S. K.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Chen, C. Y.

Clay, C. D.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

Cottone, G.

Dassel, A. C.

de Mul, F. F.

Dimou, A.

Dögnitz, N.

Essenpreis, M.

Farrell, T.

T. Farrell, M. Patterson, and B. Wilson, “A diffusion-theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys.19(4), 879–888 (1992).
[CrossRef] [PubMed]

Farrell, T. J.

T. J. Farrell, M. S. Patterson, and M. Essenpreis, “Influence of layered tissue architecture on estimates of tissue optical properties obtained from spatially resolved diffuse reflectance reflectometry,” Appl. Opt.37(10), 1958–1972 (1998).
[CrossRef]

T. J. Farrell, B. C. Wilson, and M. S. Patterson, “The use of a neural network to determine tissue optical properties from spatially resolved diffuse reflectance measurements,” Phys. Med. Biol.37(12), 2281–2286, (1992).
[CrossRef] [PubMed]

Feld, M. S.

Fitzmaurice, M.

Follen, M.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Gendron-Fitzpatrick, A.

Graaff, R.

Hayakawa, C. K.

I. S. Seo, J. S. You, C. K. Hayakawa, and V. Venugopalan, “Perturbation and differential Monte Carlo methods for measurement of optical properties in a layered epithelial tissue model,” J. Biomed. Opt.12(1), 014030 (2007).
[CrossRef] [PubMed]

Heenan, P. J.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

Hennessy, R.

R. Hennessy, S. L. Lim, M. K. Markey, and J. W. Tunnell, “Monte Carlo lookup table-based inverse model for extracting optical properties from tissue-simulating phantoms using diffuse reflectance spectroscopy,” J. Biomed. Opt.18(3), 37003 (2013).
[CrossRef]

Hibst, R.

Jacques, S.

L. Wang, S. Jacques, and L. Zheng, “CONV - convolution for responses to a finite diameter photon beam incident on multi-layered tissues,” Comput. Meth. Prog. Bio.54(3), 141–150 (1997).
[CrossRef]

Jacques, S. L.

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio.47(2), 131–146 (1995).
[CrossRef]

Jones, L. R.

Kienle, A.

Koelink, M. H.

Kollias, N.

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol.117(6), 1452–1457 (2001).
[CrossRef]

Li, Y. S.

Lilge, L.

Lim, S. L.

R. Hennessy, S. L. Lim, M. K. Markey, and J. W. Tunnell, “Monte Carlo lookup table-based inverse model for extracting optical properties from tissue-simulating phantoms using diffuse reflectance spectroscopy,” J. Biomed. Opt.18(3), 37003 (2013).
[CrossRef]

Liu, Q.

Q. Liu and N. Ramanujam, “Scaling method for fast Monte Carlo simulation of diffuse reflectance spectra from multilayered turbid media,” J. Opt. Soc. Am. A24(4), 1011–1125 (2007).
[CrossRef]

Q. Liu and N. Ramanujam, “Sequential estimation of optical properties of a two-layered epithelial tissue model from depth-resolved ultraviolet-visible diffuse reflectance spectra,” Appl. Opt.45(19), 4476–4490 (2006).
[CrossRef] [PubMed]

Malpica, A.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Manoharan, R.

Mantis, G.

Marchesini, R.

G. Zonios, A. Dimou, M. Carrara, and R. Marchesini, “In vivo optical properties of melanocytic skin lesions: common nevi, dysplastic nevi and malignant melanoma,” Photochem. Photobiol.86(1) 236–240 (2010).
[CrossRef]

Marcu, L.

Markey, M. K.

R. Hennessy, S. L. Lim, M. K. Markey, and J. W. Tunnell, “Monte Carlo lookup table-based inverse model for extracting optical properties from tissue-simulating phantoms using diffuse reflectance spectroscopy,” J. Biomed. Opt.18(3), 37003 (2013).
[CrossRef]

Migden, M. R.

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

Mirabal, Y. N.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Murphy, B. W.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

Nguyen, T. H.

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

N. Rajaram, T. H. Nguyen, and J. W. Tunnell, “Lookup table-based inverse model for determining optical properties of turbid media,” J. Biomed. Opt.13(5), 050501 (2008).
[CrossRef] [PubMed]

Nichols, B.

B. Nichols, N. Rajaram, and J. W. Tunnell, “Performance of a lookup table-based approach for measuring tissue optical properties with diffuse optical spectroscopy,” J. Biomed. Opt.17(5), 057001 (2012).
[CrossRef] [PubMed]

Palmer, G. M.

Papaioannou, T.

Parrish, J. A.

S. Wan, R. R. Anderson, and J. A. Parrish, “Analytical modeling for the optical properties of the skin with in vitro and in vivo applications,” Photochem. Photobiol.34(4), 493–499 (1981).
[PubMed]

Patterson, M.

T. Farrell, M. Patterson, and B. Wilson, “A diffusion-theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys.19(4), 879–888 (1992).
[CrossRef] [PubMed]

Patterson, M. S.

Pavlova, P.

E. Borisova, P. Troyanova, P. Pavlova, and L. Avramov, “Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy,” Quantum Electronics, 38(6), 597 (2008).
[CrossRef]

Perelman, L. T.

Pilon, L.

Preyer, N. W.

Qiyin, F.

Quirk, C. J.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

Rajaram, N.

B. Nichols, N. Rajaram, and J. W. Tunnell, “Performance of a lookup table-based approach for measuring tissue optical properties with diffuse optical spectroscopy,” J. Biomed. Opt.17(5), 057001 (2012).
[CrossRef] [PubMed]

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

N. Rajaram, T. H. Nguyen, and J. W. Tunnell, “Lookup table-based inverse model for determining optical properties of turbid media,” J. Biomed. Opt.13(5), 050501 (2008).
[CrossRef] [PubMed]

Ramanujam, N.

Reichenberg, J. S.

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

Richards-Kortum, R.

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

Ross, R.

Sampson, D. D.

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

Seo, I. S.

I. S. Seo, J. S. You, C. K. Hayakawa, and V. Venugopalan, “Perturbation and differential Monte Carlo methods for measurement of optical properties in a layered epithelial tissue model,” J. Biomed. Opt.12(1), 014030 (2007).
[CrossRef] [PubMed]

Skala, M. C.

Steiner, R.

Sung, K. B.

Svensson, T.

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Tseng, T. Y.

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N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
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I. S. Seo, J. S. You, C. K. Hayakawa, and V. Venugopalan, “Perturbation and differential Monte Carlo methods for measurement of optical properties in a layered epithelial tissue model,” J. Biomed. Opt.12(1), 014030 (2007).
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L. Wang, S. Jacques, and L. Zheng, “CONV - convolution for responses to a finite diameter photon beam incident on multi-layered tissues,” Comput. Meth. Prog. Bio.54(3), 141–150 (1997).
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A. Kienle, L. Lilge, M. S. Patterson, R. Hibst, R. Steiner, and B. C. Wilson, “Spatially resolved absolute diffuse reflectance measurements for noninvasive determination of the optical scattering and absorption coefficients of biological tissue,” Appl. Opt.35(13), 2304–2314 (1996).
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R. Graaff, M. H. Koelink, F. F. de Mul, W. G. Zijistra, A. C. Dassel, and J. G. Aarnoudse, “Condensed Monte Carlo simulations for the description of light transport,” Appl. Opt.32(4), 426–434 (1993).
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Biomed. Opt. Express (1)

Comput. Meth. Prog. Bio. (2)

L. Wang, S. Jacques, and L. Zheng, “CONV - convolution for responses to a finite diameter photon beam incident on multi-layered tissues,” Comput. Meth. Prog. Bio.54(3), 141–150 (1997).
[CrossRef]

L. Wang, S. L. Jacques, and L. Zheng, “MCML–Monte Carlo modeling of light transport in multi-layered tissues,” Comput. Meth. Prog. Bio.47(2), 131–146 (1995).
[CrossRef]

J. Biomed. Opt. (7)

R. Hennessy, S. L. Lim, M. K. Markey, and J. W. Tunnell, “Monte Carlo lookup table-based inverse model for extracting optical properties from tissue-simulating phantoms using diffuse reflectance spectroscopy,” J. Biomed. Opt.18(3), 37003 (2013).
[CrossRef]

I. S. Seo, J. S. You, C. K. Hayakawa, and V. Venugopalan, “Perturbation and differential Monte Carlo methods for measurement of optical properties in a layered epithelial tissue model,” J. Biomed. Opt.12(1), 014030 (2007).
[CrossRef] [PubMed]

N. Rajaram, T. H. Nguyen, and J. W. Tunnell, “Lookup table-based inverse model for determining optical properties of turbid media,” J. Biomed. Opt.13(5), 050501 (2008).
[CrossRef] [PubMed]

B. Nichols, N. Rajaram, and J. W. Tunnell, “Performance of a lookup table-based approach for measuring tissue optical properties with diffuse optical spectroscopy,” J. Biomed. Opt.17(5), 057001 (2012).
[CrossRef] [PubMed]

Y. N. Mirabal, S. K. Chang, E. N. Atkinson, A. Malpica, M. Follen, and R. Richards-Kortum, “Reflectance spectroscopy for in vivo detection of cervical precancer,” J. Biomed. Opt.7(4), 587–594 (2002).
[CrossRef] [PubMed]

B. W. Murphy, R. J. Webster, B. A. Turlach, C. J. Quirk, C. D. Clay, P. J. Heenan, and D. D. Sampson, “Toward the discrimination of early melanoma from common and dysplastic nevus using fiber optic diffuse reflectance spectroscopy,” J. Biomed. Opt.10(6), 064020 (2005).
[CrossRef]

E. Alerstam, T. Svensson, and S. Andersson-Engels, “Parallel computing with graphics processing units for high-speed Monte Carlo simulation of photon migration,” J. Biomed. Opt.13(6), 060504 (2008).
[CrossRef]

J. Invest. Dermatol. (1)

G. Zonios, J. Bykowski, and N. Kollias, “Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy,” J. Invest. Dermatol.117(6), 1452–1457 (2001).
[CrossRef]

J. Opt. Soc. Am. A (1)

Laser Surg. Med. (1)

N. Rajaram, J. S. Reichenberg, M. R. Migden, T. H. Nguyen, and J. W. Tunnell, “Pilot clinical study for quantitative spectral diagnosis of non-melanoma skin cancer,” Laser Surg. Med.42(10), 716–727 (2010).
[CrossRef]

Med. Phys. (1)

T. Farrell, M. Patterson, and B. Wilson, “A diffusion-theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo,” Med. Phys.19(4), 879–888 (1992).
[CrossRef] [PubMed]

Opt. Express (1)

Photochem. Photobiol. (2)

S. Wan, R. R. Anderson, and J. A. Parrish, “Analytical modeling for the optical properties of the skin with in vitro and in vivo applications,” Photochem. Photobiol.34(4), 493–499 (1981).
[PubMed]

G. Zonios, A. Dimou, M. Carrara, and R. Marchesini, “In vivo optical properties of melanocytic skin lesions: common nevi, dysplastic nevi and malignant melanoma,” Photochem. Photobiol.86(1) 236–240 (2010).
[CrossRef]

Phys. Med. Biol. (1)

T. J. Farrell, B. C. Wilson, and M. S. Patterson, “The use of a neural network to determine tissue optical properties from spatially resolved diffuse reflectance measurements,” Phys. Med. Biol.37(12), 2281–2286, (1992).
[CrossRef] [PubMed]

Quantum Electronics (1)

E. Borisova, P. Troyanova, P. Pavlova, and L. Avramov, “Diagnostics of pigmented skin tumors based on laser-induced autofluorescence and diffuse reflectance spectroscopy,” Quantum Electronics, 38(6), 597 (2008).
[CrossRef]

SIAM J. Optim. (1)

F. Alizadeh, “Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization,” SIAM J. Optim.5(1), 13–51 (1995).
[CrossRef]

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Figures (9)

Fig. 1
Fig. 1

Two-layer model geometry used in the Monte Carlo simulations. Absorption for the top and bottom layers, scattering for both layers, and the top-layer thickness are used as inputs to generate reflectance values for all SDSs. The coverslip was modeled as a middle layer with constant thickness of .625 mm, no scattering or absorption, and an index of refraction of 1.5.

Fig. 2
Fig. 2

Flowchart for the forward model of diffuse reflectance for a two-layer tissue model. Tissue parameters are inputs into the model and the output is a diffuse reflectance spectrum. The Monte Carlo lookup table is used to determine reflectance based on the set of optical properties and top layer thickness.

Fig. 3
Fig. 3

Inverse model of diffuse reflectance. First, an initial guess for the tissue parameters is used to generate a spectrum with the forward model. Next, the error between the measured and modeled spectra is calculated and the parameters are updated using an optimization routine that minimizes the error between the modeled and measured spectra.

Fig. 4
Fig. 4

Schematic of the two-layered experiment and the DRS system used to collect the data, including the “photon flow” from: excitation provided by the xenon lamp, whose signal is passed through a long-pass filter and an optical lens system for collimation and focusing into a fiber-optic switch to be delivered to the two-layer phantom, consisting of a top layer (TL) and bottom layer (BL). The bottom layer is housed in a small vial cap with a coverslip placed on top, and the top layer poured on top of it. Collection is at 370 and 740 μm SDSs and passed into a spectrograph and imaged by a cooled CCD camera. Custom software provides the trigger for the light source and detector and also processes and stores the measured spectra for later analysis.

Fig. 5
Fig. 5

Measured spectra (colored and dashed) and associated MCLUT fits (solid black) from phantom 3 with a top layer thickness of 300 μm.

Fig. 6
Fig. 6

Measured reflectance spectra at selected heights for phantom 8. Top and bottom plots correspond to 370 and 740 μm source-detector separations, respectively. Scaled absorbance profiles of red (dashed red line) and blue (dashed blue line) dyes are also included for reference.

Fig. 7
Fig. 7

Average calculated NRMSD values for each top layer thickness..

Fig. 8
Fig. 8

Comparison between measured and predicted top layer thicknesses. The error bars in the figure represent the standard deviation of the thickness prediction at each particular height. The solid line is the line of perfect agreement.

Fig. 9
Fig. 9

NRMSD for Z0 vs. known Z0 for when only one of the SDSs is used and for when both are used. This plot shows how using multiple SDSs can expand the range where Z0 can accurately be predicted.

Tables (1)

Tables Icon

Table 1 Summary of the optical properties of the two-layer phantoms used in this study for comparison with MC simulations. The scattering values are given for λ = 630 nm. For the absorbers: g is green dye; r is red dye; b is blue dye; and Hb is dissolved Hemoglobin powder. The largest source of uncertainty for the optical property values is due to errors in the pipette volumes required in order to create the liquid phantoms. The pipettes were calibrated; however, based upon vendor specifications, pipette volume uncertainties were calculated to result in approximately a 4% error in optical property values.

Equations (6)

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μ s ( λ ) = μ s ( λ 0 ) × ( λ λ 0 ) B
μ a , t ( λ ) = i = 1 N t ln ( 10 ) ε i , t ( λ ) C i , t
μ a , b ( λ ) = i = 1 N b ln ( 10 ) ε i , b ( λ ) C i , b
E = 1 n S S λ [ R s , meas ( λ ) R s , model ( λ ) R s , meas ( λ ) ] 2
R ( λ ) = I sample ( λ ) I background ( λ ) [ I standard ( λ ) I background ( λ ) ] × 100 / R standard
NRMSD = 1 x i , max x i , min i = 1 n ( x i ( Z 0 ) x ^ i ( Z 0 ) ) 2 n

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