Q. Fang and S. Yan, “Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations,” J. Biomed. Opt. 24(11), 1 (2019).

[Crossref]

B. H. Hokr, V. V. Yakovlev, and M. O. Scully, “Efficient time-dependent Monte Carlo simulations of stimulated raman scattering in a turbid medium,” ACS Photonics 1(12), 1322–1329 (2014).

[Crossref]

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

T. P. Moffitt, Y. Chen, and S. A. Prahl, “Preparation and characterization of polyurethane optical phantoms.,” J. Biomed. Opt. 11(4), 041103 (2006).

[Crossref]

C. J. Hourdakis and A. Perris, “A Monte Carlo estimation of tissue optical properties for use in laser dosimetry,” Phys. Med. Biol. 40(3), 351–364 (1995).

[Crossref]

L. Wang, S. L. Jacques, and L. Zheng, “MCML - Monte Carlo modeling of tight transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).

[Crossref]

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

M. J. D. Powell, “An efficient method for finding the minimum of a function of several variables without calculating derivatives,” The Comput. J. 7(2), 155–162 (1964).

[Crossref]

R. Brent, Algorithms for Minimization Without Derivatives (Dover, 2002).

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

J. Burkardt, “PRAXIS - scalar function optimization,” (2016). [Online; accessed 2019].

T. P. Moffitt, Y. Chen, and S. A. Prahl, “Preparation and characterization of polyurethane optical phantoms.,” J. Biomed. Opt. 11(4), 041103 (2006).

[Crossref]

P. Lemaillet, C. C. Cooksey, J. Hwang, H. Wabnitz, D. Grosenick, L. Yang, and D. W. Allen, “Correction of an adding-doubling inversion algorithm for the measurement of the optical parameters of turbid media,” Biomed. Opt. Express 9(1), 55–71 (2018).

[Crossref]

Z. H. Levine, R. H. Streater, A.-M. R. Lieberson, A. L. Pintar, C. C. Cooksey, and P. Lemaillet, “Algorithm for rapid determination of optical scattering parameters,” Opt. Express 25(22), 26728–26746 (2017).

[Crossref]

Q. Fang and S. Yan, “Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations,” J. Biomed. Opt. 24(11), 1 (2019).

[Crossref]

P. Q. Fiee, “Double integrating sphere characterization of pva-cryogels,” Master’s thesis, McMaster University (2015).

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

R. G. Giovanelli, “Reflection by semi-infinite diffusers,” Opt. Acta 2(4), 153–162 (1955).

[Crossref]

B. H. Hokr, V. V. Yakovlev, and M. O. Scully, “Efficient time-dependent Monte Carlo simulations of stimulated raman scattering in a turbid medium,” ACS Photonics 1(12), 1322–1329 (2014).

[Crossref]

C. J. Hourdakis and A. Perris, “A Monte Carlo estimation of tissue optical properties for use in laser dosimetry,” Phys. Med. Biol. 40(3), 351–364 (1995).

[Crossref]

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

L. Wang, S. L. Jacques, and L. Zheng, “MCML - Monte Carlo modeling of tight transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).

[Crossref]

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

E. Jones, T. Oliphant, and P. Peterson, “SciPy: Open source scientific tools for Python,” (2001). [Online; accessed 2018-2019].

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

B. N. Taylor and C. E. Kuyatt, “Guidelines for evaluating and expressing the uncertainty of NIST measurement results,” Tech. rep., National Institute of Standards and Technology, Gaithersburg, Maryland (1994).

P. Lemaillet, C. C. Cooksey, J. Hwang, H. Wabnitz, D. Grosenick, L. Yang, and D. W. Allen, “Correction of an adding-doubling inversion algorithm for the measurement of the optical parameters of turbid media,” Biomed. Opt. Express 9(1), 55–71 (2018).

[Crossref]

Z. H. Levine, R. H. Streater, A.-M. R. Lieberson, A. L. Pintar, C. C. Cooksey, and P. Lemaillet, “Algorithm for rapid determination of optical scattering parameters,” Opt. Express 25(22), 26728–26746 (2017).

[Crossref]

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

A. D. Polyanin and A. V. Manzhirov, Handbook of Mathematics for Engineers and Scientists (Taylor & Francis, 2006).

T. P. Moffitt, Y. Chen, and S. A. Prahl, “Preparation and characterization of polyurethane optical phantoms.,” J. Biomed. Opt. 11(4), 041103 (2006).

[Crossref]

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

E. Jones, T. Oliphant, and P. Peterson, “SciPy: Open source scientific tools for Python,” (2001). [Online; accessed 2018-2019].

C. J. Hourdakis and A. Perris, “A Monte Carlo estimation of tissue optical properties for use in laser dosimetry,” Phys. Med. Biol. 40(3), 351–364 (1995).

[Crossref]

E. Jones, T. Oliphant, and P. Peterson, “SciPy: Open source scientific tools for Python,” (2001). [Online; accessed 2018-2019].

A. D. Polyanin and A. V. Manzhirov, Handbook of Mathematics for Engineers and Scientists (Taylor & Francis, 2006).

M. J. D. Powell, “An efficient method for finding the minimum of a function of several variables without calculating derivatives,” The Comput. J. 7(2), 155–162 (1964).

[Crossref]

T. P. Moffitt, Y. Chen, and S. A. Prahl, “Preparation and characterization of polyurethane optical phantoms.,” J. Biomed. Opt. 11(4), 041103 (2006).

[Crossref]

S. A. Prahl, M. J. C. van Gemert, and A. J. Welch, “Determining the optical properties of turbid media by using the adding–doubling method,” Appl. Opt. 32(4), 559–568 (1993).

[Crossref]

J. W. Pickering, C. J. M. Moes, H. J. C. M. Sterenborg, S. A. Prahl, and M. J. C. van Gemert, “Two integrating spheres with an intervening scattering sample,” J. Opt. Soc. Am. A 9(4), 621–631 (1992).

[Crossref]

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

S. A. Prahl, “Light transport in tissue,” Ph.D. thesis, The University of Texas at Austin (1988).

S. A. Prahl, “Everything I think you should know about inverse adding-doubling,” (2011). [Online; accessed 2018-2019].

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

S. L. Storm, A. Springsteen, and T. M. Ricker, “A discussion of center mount sample holder designs and applications,” Tech. rep., Labsphere (1998).

B. H. Hokr, V. V. Yakovlev, and M. O. Scully, “Efficient time-dependent Monte Carlo simulations of stimulated raman scattering in a turbid medium,” ACS Photonics 1(12), 1322–1329 (2014).

[Crossref]

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

S. L. Storm, A. Springsteen, and T. M. Ricker, “A discussion of center mount sample holder designs and applications,” Tech. rep., Labsphere (1998).

S. L. Storm, A. Springsteen, and T. M. Ricker, “A discussion of center mount sample holder designs and applications,” Tech. rep., Labsphere (1998).

B. N. Taylor and C. E. Kuyatt, “Guidelines for evaluating and expressing the uncertainty of NIST measurement results,” Tech. rep., National Institute of Standards and Technology, Gaithersburg, Maryland (1994).

J. R. Taylor, An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements, 2nd ed (University Science Books, 1996).

H. C. van de Hulst, Multiple Light Scattering, vol. 2 (Academic Press, 1980).

S. A. Prahl, M. J. C. van Gemert, and A. J. Welch, “Determining the optical properties of turbid media by using the adding–doubling method,” Appl. Opt. 32(4), 559–568 (1993).

[Crossref]

J. W. Pickering, C. J. M. Moes, H. J. C. M. Sterenborg, S. A. Prahl, and M. J. C. van Gemert, “Two integrating spheres with an intervening scattering sample,” J. Opt. Soc. Am. A 9(4), 621–631 (1992).

[Crossref]

L. Wang, S. L. Jacques, and L. Zheng, “MCML - Monte Carlo modeling of tight transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).

[Crossref]

S. A. Prahl, M. J. C. van Gemert, and A. J. Welch, “Determining the optical properties of turbid media by using the adding–doubling method,” Appl. Opt. 32(4), 559–568 (1993).

[Crossref]

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

B. H. Hokr, V. V. Yakovlev, and M. O. Scully, “Efficient time-dependent Monte Carlo simulations of stimulated raman scattering in a turbid medium,” ACS Photonics 1(12), 1322–1329 (2014).

[Crossref]

Q. Fang and S. Yan, “Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations,” J. Biomed. Opt. 24(11), 1 (2019).

[Crossref]

L. Wang, S. L. Jacques, and L. Zheng, “MCML - Monte Carlo modeling of tight transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).

[Crossref]

B. H. Hokr, V. V. Yakovlev, and M. O. Scully, “Efficient time-dependent Monte Carlo simulations of stimulated raman scattering in a turbid medium,” ACS Photonics 1(12), 1322–1329 (2014).

[Crossref]

P. Lemaillet, C. C. Cooksey, J. Hwang, H. Wabnitz, D. Grosenick, L. Yang, and D. W. Allen, “Correction of an adding-doubling inversion algorithm for the measurement of the optical parameters of turbid media,” Biomed. Opt. Express 9(1), 55–71 (2018).

[Crossref]

A. Doronin and I. Meglinski, “Online object oriented Monte Carlo computational tool for the needs of biomedical optics,” Biomed. Opt. Express 2(9), 2461–2469 (2011).

[Crossref]

L. Wang, S. L. Jacques, and L. Zheng, “MCML - Monte Carlo modeling of tight transport in multi-layered tissues,” Comput. Methods Programs Biomed. 47(2), 131–146 (1995).

[Crossref]

T. P. Moffitt, Y. Chen, and S. A. Prahl, “Preparation and characterization of polyurethane optical phantoms.,” J. Biomed. Opt. 11(4), 041103 (2006).

[Crossref]

Q. Fang and S. Yan, “Graphics processing unit-accelerated mesh-based Monte Carlo photon transport simulations,” J. Biomed. Opt. 24(11), 1 (2019).

[Crossref]

R. G. Giovanelli, “Reflection by semi-infinite diffusers,” Opt. Acta 2(4), 153–162 (1955).

[Crossref]

C. J. Hourdakis and A. Perris, “A Monte Carlo estimation of tissue optical properties for use in laser dosimetry,” Phys. Med. Biol. 40(3), 351–364 (1995).

[Crossref]

J. Nickolls, I. Buck, M. Garland, and K. Skadron, “Scalable parallel programming with CUDA,” Queue 6(2), 40–53 (2008).

[Crossref]

S. A. Prahl, M. Keijzer, S. L. Jacques, and A. J. Welch, “A Monte Carlo model of light propagation in tissue,” SPIE Institute Series 5, 102–111 (1989).

M. J. D. Powell, “An efficient method for finding the minimum of a function of several variables without calculating derivatives,” The Comput. J. 7(2), 155–162 (1964).

[Crossref]

J. Burkardt, “PRAXIS - scalar function optimization,” (2016). [Online; accessed 2019].

E. Jones, T. Oliphant, and P. Peterson, “SciPy: Open source scientific tools for Python,” (2001). [Online; accessed 2018-2019].

R. Brent, Algorithms for Minimization Without Derivatives (Dover, 2002).

B. N. Taylor and C. E. Kuyatt, “Guidelines for evaluating and expressing the uncertainty of NIST measurement results,” Tech. rep., National Institute of Standards and Technology, Gaithersburg, Maryland (1994).

P. Q. Fiee, “Double integrating sphere characterization of pva-cryogels,” Master’s thesis, McMaster University (2015).

H. C. van de Hulst, Multiple Light Scattering, vol. 2 (Academic Press, 1980).

“Report of calibration special photometric tests for four synthetic adult skin samples and one synthetic bulk fat sample,” Tech. rep., National Institute of Standards and Technology, Gaithersburg, Maryland (2017).

S. L. Storm, A. Springsteen, and T. M. Ricker, “A discussion of center mount sample holder designs and applications,” Tech. rep., Labsphere (1998).

S. A. Prahl, “Light transport in tissue,” Ph.D. thesis, The University of Texas at Austin (1988).

“Integrating sphere theory and applications,” Tech. rep., Labsphere (2017). [Online; accessed 2019].

A. D. Polyanin and A. V. Manzhirov, Handbook of Mathematics for Engineers and Scientists (Taylor & Francis, 2006).

J. R. Taylor, An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements, 2nd ed (University Science Books, 1996).

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S. A. Prahl, “Everything I think you should know about inverse adding-doubling,” (2011). [Online; accessed 2018-2019].

F. E. Nicodemus, J. C. Richmond, J. J. Hsia, I. W. Ginsberg, and T. Limperis, “Geometrical considerations and nomenclature for reflectance,” Natl. Bur. Stand.160, 94–145 (1977).

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