Abstract

Hyperspectral images of tissue contain extensive and complex information relevant for clinical applications. In this work, wavelet decomposition is explored for feature extraction from such data. Wavelet methods are simple and computationally effective, and can be implemented in real-time. The aim of this study was to correlate results from wavelet decomposition in the spectral domain with physical parameters (tissue oxygenation, blood and melanin content). Wavelet decomposition was tested on Monte Carlo simulations, measurements of a tissue phantom and hyperspectral data from a human volunteer during an occlusion experiment. Reflectance spectra were decomposed, and the coefficients were correlated to tissue parameters. This approach was used to identify wavelet components that can be utilized to map levels of blood, melanin and oxygen saturation. The results show a significant correlation (p <0.02) between the chosen tissue parameters and the selected wavelet components. The tissue parameters could be mapped using a subset of the calculated components due to redundancy in spectral information. Vessel structures are well visualized. Wavelet analysis appears as a promising tool for extraction of spectral features in skin. Future studies will aim at developing quantitative mapping of optical properties based on wavelet decomposition.

© 2014 Optical Society of America

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References

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2014 (1)

A. Bjorgan, M. Milanic, and L. L. Randeberg, “Estimation of skin optical parameters for real-time hyperspectral imaging applications,” J. Biomed. Opt. 19, 066003 (2014).
[Crossref] [PubMed]

2013 (3)

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
[Crossref]

P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
[Crossref]

S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R59 (2013).
[Crossref] [PubMed]

2012 (1)

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
[Crossref]

2011 (3)

P. C. Chen and W. C. Lin, “Spectral-profile-based algorithm for hemoglobin oxygen saturation determination from diffuse reflectance spectra,” Biomed. Opt. Express 2, 1082–1096 (2011).
[Crossref] [PubMed]

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: A review,” J. Innov. Opt. Health Sci. 4, 9–38 (2011).
[Crossref]

M. Milanic and B. Majaron, “Three-dimensional monte carlo model of pulsed-laser treatment of cutaneous vascular lesions,” J. Biomed. Opt. 16, 128002 (2011).
[Crossref] [PubMed]

2010 (2)

2009 (1)

L. L. Randeberg, E. L. P. Larsen, and L. O. Svaasand, “Hyperspectral imaging of blood perfusion and chromophore distribution in skin,” Proc. SPIE 7161, 71610C (2009).
[Crossref]

2008 (2)

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
[Crossref]

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
[Crossref]

2006 (3)

T. Skauli, P. E. Goa, I. Baarstad, and T. Løke, “A compact combined hyperspectral and polarimetric imager,” Proc. SPIE 6395, 639505 (2006).
[Crossref]

E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
[Crossref]

M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
[Crossref]

2005 (3)

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
[Crossref]

G. Camps-Valls and L. Bruzzone, “Kernel-based methods for hyperspectral image classification,” IEEE T. Geosci. Remote 43, 1351–1362 (2005).
[Crossref]

2004 (1)

G. N. Stamatas and N. Kollias, “Blood stasis contributions to the perception of skin pigmentation,” J. Biomed. Opt. 9, 315–322 (2004).
[Crossref] [PubMed]

2002 (1)

L. M. Bruce, C. H. Koger, and J. Li, “Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,” IEEE Trans. Geosci. Remote 40, 2331–2338 (2002).
[Crossref]

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, 1452–1457 (2001).
[Crossref]

1997 (1)

T. Spott, L. O. Svaasand, R. E. Anderson, and P. F. Schmedling, “Application of optical diffusion theory to transcutaneous bilirubinometry,” Proc. SPIE 3195, 234–245 (1997).
[Crossref]

1995 (2)

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
[Crossref]

R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
[Crossref] [PubMed]

1989 (1)

S. G. Mallat, “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. 11, 674–693 (1989).
[Crossref]

1988 (1)

A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
[Crossref]

1981 (1)

R. Anderson and J. Parrish, “The optics of human skin,” J. Invest. Dermatol. 77, 13–19 (1981).
[Crossref] [PubMed]

1980 (1)

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Alerstam, E.

Anderson, R.

R. Anderson and J. Parrish, “The optics of human skin,” J. Invest. Dermatol. 77, 13–19 (1981).
[Crossref] [PubMed]

Anderson, R. E.

T. Spott, L. O. Svaasand, R. E. Anderson, and P. F. Schmedling, “Application of optical diffusion theory to transcutaneous bilirubinometry,” Proc. SPIE 3195, 234–245 (1997).
[Crossref]

Anderson, R. R.

R. R. Anderson and J. A. Parrish, The Science of Photomedicine (Plenum Press, 1982), chap. 6: Optical properties of human skin, pp. 147–194.
[Crossref]

Andersson-Engels, S.

Baarstad, I.

T. Skauli, P. E. Goa, I. Baarstad, and T. Løke, “A compact combined hyperspectral and polarimetric imager,” Proc. SPIE 6395, 639505 (2006).
[Crossref]

Barker, D. J.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Bashkatov, A. N.

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: A review,” J. Innov. Opt. Health Sci. 4, 9–38 (2011).
[Crossref]

A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
[Crossref]

Beer, J. Z.

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
[Crossref]

Benediktsson, J. A.

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
[Crossref]

Berman, M.

A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
[Crossref]

Berns, M. W.

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
[Crossref]

Bjorgan, A.

A. Bjorgan, M. Milanic, and L. L. Randeberg, “Estimation of skin optical parameters for real-time hyperspectral imaging applications,” J. Biomed. Opt. 19, 066003 (2014).
[Crossref] [PubMed]

Boggess, A.

A. Boggess and F. J. Narcowich, A First Course in Wavelets with Fourier Analysis, 2nd ed. (Wiley, 2009).

Bruce, L. M.

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
[Crossref]

L. M. Bruce, C. H. Koger, and J. Li, “Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,” IEEE Trans. Geosci. Remote 40, 2331–2338 (2002).
[Crossref]

T. R. West, S. Prasad, and L. M. Bruce, “Wavelet packet tree pruning metrics for hyperspectral feature extraction,” in Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008 (IEEE, 2008), pp. II–946–II–949.

Bruzzone, L.

G. Camps-Valls and L. Bruzzone, “Kernel-based methods for hyperspectral image classification,” IEEE T. Geosci. Remote 43, 1351–1362 (2005).
[Crossref]

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, 1452–1457 (2001).
[Crossref]

Camps-Valls, G.

G. Camps-Valls and L. Bruzzone, “Kernel-based methods for hyperspectral image classification,” IEEE T. Geosci. Remote 43, 1351–1362 (2005).
[Crossref]

Chance, B.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Chanussot, J.

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
[Crossref]

Chen, P. C.

Cotterill, J. A.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Craig, M.

A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
[Crossref]

Cubeddu, R.

R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, and R. Cubeddu, “Determination of vis- nir absorptioncoefficients of mammalian fat, with time- and spatially resolved diffusereflectance and transmission spectroscopy,”(OSA, 2004).

Daubechies, I.

I. Daubechies, Ten Lectures on Wavelets, no. 61 in CBMS/NSF Series in Applied Math. (1992).
[Crossref]

Dawson, J. B.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

De Blasi, R. A.

R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
[Crossref] [PubMed]

Denstedt, M.

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
[Crossref]

Descombes, X.

S. Prigent, X. Descombes, D. Zugaj, and J. Zerubia, “Spectral analysis and unsupervised svm classification for skin hyper-pigmentation classification,” in “2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program,” (2010).

Durduran, T.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Ellis, D. J.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Fantini, S.

R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
[Crossref] [PubMed]

Fauvel, M.

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
[Crossref]

Feather, J. W.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Ferrari, M.

R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
[Crossref] [PubMed]

Fisher, G. W.

J. B. Dawson, D. J. Barker, D. J. Ellis, J. A. Cotterill, E. Grassam, G. W. Fisher, and J. W. Feather, “A theoretical and experimental study of light absorption and scattering by in vivo skin,” Phys. Med. Biol. 25, 695–709 (1980).
[Crossref] [PubMed]

Fiskerstrand, E. J.

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
[Crossref]

Fowler, J. E.

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
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R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
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M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
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A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: A review,” J. Innov. Opt. Health Sci. 4, 9–38 (2011).
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A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
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T. Skauli, P. E. Goa, I. Baarstad, and T. Løke, “A compact combined hyperspectral and polarimetric imager,” Proc. SPIE 6395, 639505 (2006).
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R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
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A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
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Han, T. D.

Hernandez-Palacios, J. E.

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
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S. L. Jacques, “Optical properties of biological tissues: a review,” Phys. Med. Biol. 58, R37–R59 (2013).
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E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
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Kochubey, V. I.

A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
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Koger, C. H.

L. M. Bruce, C. H. Koger, and J. Li, “Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,” IEEE Trans. Geosci. Remote 40, 2331–2338 (2002).
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Kollias, N.

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
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G. N. Stamatas and N. Kollias, “Blood stasis contributions to the perception of skin pigmentation,” J. Biomed. Opt. 9, 315–322 (2004).
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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, 1452–1457 (2001).
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Larsen, E. L. P.

L. L. Randeberg, E. L. P. Larsen, and L. O. Svaasand, “Hyperspectral imaging of blood perfusion and chromophore distribution in skin,” Proc. SPIE 7161, 71610C (2009).
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Lech, G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
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Li, H.

H. Li, L. Lin, and S. Xie, “Refractive index of human whole blood with different types in the visible and near-infrared ranges,” Proc. SPIE3914 (2000).
[Crossref]

Li, J.

L. M. Bruce, C. H. Koger, and J. Li, “Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,” IEEE Trans. Geosci. Remote 40, 2331–2338 (2002).
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Li, W.

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
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Lin, L.

H. Li, L. Lin, and S. Xie, “Refractive index of human whole blood with different types in the visible and near-infrared ranges,” Proc. SPIE3914 (2000).
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Lo, W. C. Y.

Løke, T.

T. Skauli, P. E. Goa, I. Baarstad, and T. Løke, “A compact combined hyperspectral and polarimetric imager,” Proc. SPIE 6395, 639505 (2006).
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Majaron, B.

P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
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M. Milanic and B. Majaron, “Three-dimensional monte carlo model of pulsed-laser treatment of cutaneous vascular lesions,” J. Biomed. Opt. 16, 128002 (2011).
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S. G. Mallat, “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. 11, 674–693 (1989).
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M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
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Milanic, M.

A. Bjorgan, M. Milanic, and L. L. Randeberg, “Estimation of skin optical parameters for real-time hyperspectral imaging applications,” J. Biomed. Opt. 19, 066003 (2014).
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P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
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M. Milanic and B. Majaron, “Three-dimensional monte carlo model of pulsed-laser treatment of cutaneous vascular lesions,” J. Biomed. Opt. 16, 128002 (2011).
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Mohler, E. R.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
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Mueller, G.

M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
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Naglic, P.

P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
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L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
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D. Yudovsky, A. Nouvong, and L. Pilon, “Hyperspectral imaging in diabetic foot wound care,” J. Diabetes Sci. Technol. 4, 1099–1113 (2010).
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Novak, J.

E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
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Paluchowski, L.

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
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R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, and R. Cubeddu, “Determination of vis- nir absorptioncoefficients of mammalian fat, with time- and spatially resolved diffusereflectance and transmission spectroscopy,”(OSA, 2004).

Pilon, L.

D. Yudovsky, A. Nouvong, and L. Pilon, “Hyperspectral imaging in diabetic foot wound care,” J. Diabetes Sci. Technol. 4, 1099–1113 (2010).
[Crossref] [PubMed]

Prasad, S.

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
[Crossref]

T. R. West, S. Prasad, and L. M. Bruce, “Wavelet packet tree pruning metrics for hyperspectral feature extraction,” in Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008 (IEEE, 2008), pp. II–946–II–949.

Prigent, S.

S. Prigent, X. Descombes, D. Zugaj, and J. Zerubia, “Spectral analysis and unsupervised svm classification for skin hyper-pigmentation classification,” in “2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program,” (2010).

Pukstad, B. S.

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
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K. Rajpoot and N. M. Rajpoot, “Hyperspectral colon tissue cell classification,” in “SPIE Medical Imaging,” (2010).

Randeberg, L. L.

A. Bjorgan, M. Milanic, and L. L. Randeberg, “Estimation of skin optical parameters for real-time hyperspectral imaging applications,” J. Biomed. Opt. 19, 066003 (2014).
[Crossref] [PubMed]

M. Denstedt, B. S. Pukstad, L. Paluchowski, J. E. Hernandez-Palacios, and L. L. Randeberg, “Hyperspectral imaging as a diagnostic tool for chronic skin ulcers,” Proc. SPIE 8565, 85650N (2013).
[Crossref]

P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
[Crossref]

L. L. Randeberg, E. L. P. Larsen, and L. O. Svaasand, “Hyperspectral imaging of blood perfusion and chromophore distribution in skin,” Proc. SPIE 7161, 71610C (2009).
[Crossref]

Roggan, A.

M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
[Crossref]

Rose, J.

Salomatina, E.

E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
[Crossref]

Schmedling, P. F.

T. Spott, L. O. Svaasand, R. E. Anderson, and P. F. Schmedling, “Application of optical diffusion theory to transcutaneous bilirubinometry,” Proc. SPIE 3195, 234–245 (1997).
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D. SegelsteinThe complex refractive index of water, Master'sthesis, University of Missouri-Kansas City (1981).

Skauli, T.

T. Skauli, P. E. Goa, I. Baarstad, and T. Løke, “A compact combined hyperspectral and polarimetric imager,” Proc. SPIE 6395, 639505 (2006).
[Crossref]

Spott, T.

T. Spott, L. O. Svaasand, R. E. Anderson, and P. F. Schmedling, “Application of optical diffusion theory to transcutaneous bilirubinometry,” Proc. SPIE 3195, 234–245 (1997).
[Crossref]

Stamatas, G. N.

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
[Crossref]

G. N. Stamatas and N. Kollias, “Blood stasis contributions to the perception of skin pigmentation,” J. Biomed. Opt. 9, 315–322 (2004).
[Crossref] [PubMed]

Sterenborg, H. J. C. M.

R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, and R. Cubeddu, “Determination of vis- nir absorptioncoefficients of mammalian fat, with time- and spatially resolved diffusereflectance and transmission spectroscopy,”(OSA, 2004).

Stopps, E. K. S.

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
[Crossref]

Svaasand, L. O.

L. L. Randeberg, E. L. P. Larsen, and L. O. Svaasand, “Hyperspectral imaging of blood perfusion and chromophore distribution in skin,” Proc. SPIE 7161, 71610C (2009).
[Crossref]

T. Spott, L. O. Svaasand, R. E. Anderson, and P. F. Schmedling, “Application of optical diffusion theory to transcutaneous bilirubinometry,” Proc. SPIE 3195, 234–245 (1997).
[Crossref]

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
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Sveinsson, J. R.

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
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Switzer, P.

A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
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Torricelli, A.

R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, and R. Cubeddu, “Determination of vis- nir absorptioncoefficients of mammalian fat, with time- and spatially resolved diffusereflectance and transmission spectroscopy,”(OSA, 2004).

Tuchin, V. V.

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: A review,” J. Innov. Opt. Health Sci. 4, 9–38 (2011).
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A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
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van Veen, R. L. P.

R. L. P. van Veen, H. J. C. M. Sterenborg, A. Pifferi, A. Torricelli, and R. Cubeddu, “Determination of vis- nir absorptioncoefficients of mammalian fat, with time- and spatially resolved diffusereflectance and transmission spectroscopy,”(OSA, 2004).

Vidovic, L.

P. Naglic, L. Vidovic, M. Milanic, L. L. Randeberg, and B. Majaron, “Applicability of diffusion approximation in analysis of diffuse reflectance spectra from healthy human skin,” Proc. SPIE 9032, 90320N (2013).
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West, T. R.

T. R. West, S. Prasad, and L. M. Bruce, “Wavelet packet tree pruning metrics for hyperspectral feature extraction,” in Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008 (IEEE, 2008), pp. II–946–II–949.

Xie, S.

H. Li, L. Lin, and S. Xie, “Refractive index of human whole blood with different types in the visible and near-infrared ranges,” Proc. SPIE3914 (2000).
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Yaroslavsky, A. N.

E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
[Crossref]

Yodh, A. G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
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Yu, G.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Yudovsky, D.

D. Yudovsky, A. Nouvong, and L. Pilon, “Hyperspectral imaging in diabetic foot wound care,” J. Diabetes Sci. Technol. 4, 1099–1113 (2010).
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Zerubia, J.

S. Prigent, X. Descombes, D. Zugaj, and J. Zerubia, “Spectral analysis and unsupervised svm classification for skin hyper-pigmentation classification,” in “2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program,” (2010).

Zhou, C.

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

Zmudzka, B. Z.

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
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Zonios, G.

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, 1452–1457 (2001).
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Zugaj, D.

S. Prigent, X. Descombes, D. Zugaj, and J. Zerubia, “Spectral analysis and unsupervised svm classification for skin hyper-pigmentation classification,” in “2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2010 - Workshop Program,” (2010).

Biomed. Opt. Express (2)

Brit. J. Dermatol. (1)

G. N. Stamatas, B. Z. Zmudzka, N. Kollias, and J. Z. Beer, “In vivo measurement of skin erythema and pigmentation: New means of implementation of diffuse reflectance spectroscopy with a commercial instrument,” Brit. J. Dermatol. 159, 683–690 (2008).
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IEEE T. Geosci. Remote (1)

G. Camps-Valls and L. Bruzzone, “Kernel-based methods for hyperspectral image classification,” IEEE T. Geosci. Remote 43, 1351–1362 (2005).
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IEEE Trans. Geosci. Remote (3)

M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, “Spectral and spatial classification of hyper-spectral data using svms and morphological profiles,” IEEE Trans. Geosci. Remote 46, 3804–3814 (2008).
[Crossref]

L. M. Bruce, C. H. Koger, and J. Li, “Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction,” IEEE Trans. Geosci. Remote 40, 2331–2338 (2002).
[Crossref]

A. A. Green, M. Berman, P. Switzer, and M. Craig, “Transformation for ordering multispectral data in terms of image quality with implications for noise removal,” IEEE Trans. Geosci. Remote 26, 65–74 (1988).
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IEEE Trans. Pattern Anal. (1)

S. G. Mallat, “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. 11, 674–693 (1989).
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IEEE. Trans. Geosci. Remote (1)

S. Prasad, W. Li, J. E. Fowler, and L. M. Bruce, “Information fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification,” IEEE. Trans. Geosci. Remote 50, 3474–3486 (2012).
[Crossref]

J. Biomed. Opt. (6)

A. Bjorgan, M. Milanic, and L. L. Randeberg, “Estimation of skin optical parameters for real-time hyperspectral imaging applications,” J. Biomed. Opt. 19, 066003 (2014).
[Crossref] [PubMed]

E. Salomatina, B. Jian, J. Novak, and A. N. Yaroslavsky, “Optical properties of normal and cancerous human skin in the visible and near-infrared spectral range,” J. Biomed. Opt. 11, 064026 (2006).
[Crossref]

M. Milanic and B. Majaron, “Three-dimensional monte carlo model of pulsed-laser treatment of cutaneous vascular lesions,” J. Biomed. Opt. 16, 128002 (2011).
[Crossref] [PubMed]

M. Friebel, A. Roggan, G. Mueller, and M. Meinke, “Determination of optical properties of human blood in the spectral range 250 to 1100 nm using monte carlo simulation with hematocrit-dependence effective scattering phase functions,” J. Biomed. Opt. 11, 034021 (2006).
[Crossref]

G. N. Stamatas and N. Kollias, “Blood stasis contributions to the perception of skin pigmentation,” J. Biomed. Opt. 9, 315–322 (2004).
[Crossref] [PubMed]

G. Yu, T. Durduran, G. Lech, C. Zhou, B. Chance, E. R. Mohler, and A. G. Yodh, “Time-dependent blood flow and oxygenation in human skeletal muscles measured with noninvasive near-infrared diffuse optical spectroscopies,” J. Biomed. Opt. 10, 024027 (2005).
[Crossref] [PubMed]

J. Diabetes Sci. Technol. (1)

D. Yudovsky, A. Nouvong, and L. Pilon, “Hyperspectral imaging in diabetic foot wound care,” J. Diabetes Sci. Technol. 4, 1099–1113 (2010).
[Crossref] [PubMed]

J. Innov. Opt. Health Sci. (1)

A. N. Bashkatov, E. A. Genina, and V. V. Tuchin, “Optical properties of skin, subcutaneous, and muscle tissues: A review,” J. Innov. Opt. Health Sci. 4, 9–38 (2011).
[Crossref]

J. Invest. Dermatol. (2)

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, 1452–1457 (2001).
[Crossref]

R. Anderson and J. Parrish, “The optics of human skin,” J. Invest. Dermatol. 77, 13–19 (1981).
[Crossref] [PubMed]

J. Phys. D Appl. Phys. (1)

A. N. Bashkatov, E. A. Genina, V. I. Kochubey, and V. V. Tuchin, “Optical properties of human skin, subcutaneous and mucous tissues in the wavelength range from 400 to 2000 nm,” J. Phys. D Appl. Phys. 38, 2543–2555 (2005).
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Laser Med. Sci. (1)

L. O. Svaasand, L. T. Norvang, E. J. Fiskerstrand, E. K. S. Stopps, M. W. Berns, and J. S. Nelson, “Tissue parameters determining the visual appearance of normal skin and port-wine stains,” Laser Med. Sci. 10, 55–65 (1995).
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Med. Biol. Eng. Comput. (1)

R. A. De Blasi, S. Fantini, M. A. Franceschini, M. Ferrari, and E. Gratton, “Cerebral and muscle oxygen saturation measurement by frequency-domain near-infra-red spectrometer,” Med. Biol. Eng. Comput. 33, 228–230 (1995).
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Figures (16)

Fig. 1
Fig. 1 (a): Absorption coefficients of oxygenated and deoxygenated hemoglobin [14] and melanin [11]. (b): Absorption coefficients of water [15] and mammalian fat [16]. Note that the two figures have different scales. Sample reflectance generated using a Monte Carlo model is shown in (c). See also Fig. 7 and 11 for further examples of diffuse reflectance spectra. The scattering models are plotted in (d).
Fig. 2
Fig. 2 High and low-pass filtering (filters g and h, respectively) followed by down-sampling, produces approximation and detail signals. In the first step of the algorithm, the original signal is decomposed, then the process is iterated and repeatedly applied to the new approximation.
Fig. 3
Fig. 3 Reflectance signal r decomposed in 6 iterations using the high-pass filter g and low-pass filter h associated with the Symlet wavelet [20]. Reconstructed approximation and detail components are shown. The coefficients of all levels of detail and the coarsest approximation are kept in the implemented algorithm (marked by the red frame).
Fig. 4
Fig. 4 The symlet-4 wavelet function. Its resemblance to the blood absorption features of skin reflectance ensures that important features in the reflectance are captured efficiently.
Fig. 5
Fig. 5 Phantom design. The phantom design was previously published by Randeberg et al. [22]. Capillary tubes filled with blood were placed in a bath filled with a 10% intralipid/water solution.
Fig. 6
Fig. 6 Vessel model for 3D Monte Carlo simulations. The figures are not to scale.
Fig. 7
Fig. 7 Diffuse reflectance spectra, simulated using a three-layer Monte Carlo model and scattering alternative I. The spectra in (a) represent tissues with different dermal blood content. The effects of varying melanin content in epidermis are shown in (b). In (c), the effect of varying oxygen saturation levels in dermal blood can be seen.
Fig. 8
Fig. 8 Comparison between diffuse reflectance spectra simulated using scattering alternative I and II. Oxygen saturation was 99%.
Fig. 9
Fig. 9 DWT coefficients obtained from the 3D Monte Carlo simulations. Results obtained from the mole are shown in figures 9(a) to 9(c). Results obtained from the deep vessels are shown in Figs. 9(d) to 9(f). The results from the vessels going from the superficial layers to the deep layers are shown in Figs. 9(g) to 9(i). See Fig. 6 for the vessel geometry. Note that some of the coefficients have different intensity ranges in order to enhance features.
Fig. 10
Fig. 10 DWT cofficients obtained from the phantom data.
Fig. 11
Fig. 11 Diffuse reflectance spectra, collected before, during and after occlusion.
Fig. 12
Fig. 12 DWT approximation, coefficient 09 for measured data. 960 nm.
Fig. 13
Fig. 13 DWT detail 2, coefficient 17 for the measured data. 627 nm.
Fig. 14
Fig. 14 DWT approximation coefficients 4 and 5, and the difference between them, which emphasizes melanin content. Image acquired before occlusion.
Fig. 15
Fig. 15 DWT approximation coefficient 05 minus coefficient 04, correlation to melanin, blood and oxygenation, as applied on simulated 1D Monte Carlo spectra.
Fig. 16
Fig. 16 Comparison between DWT-based and traditional melanin indices.

Tables (3)

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Table 1 Parameter combinations of the simulated spectra. All spectra were simulated using both scattering models.

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Table 2 Correlation between input parameters and a few selected DWT coefficients. Correlation coefficients R and probabilities p have been calculated for varying input parameters and output DWT coefficients of the simulated spectra as described in section 2.6. λ is the approximate center wavelength for the DWT coefficient.

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Table 3 Calculated oxygen saturation levels and blood volume fractions for plain skin before, during and after occlusion.

Equations (6)

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W ψ r ( j , k ) = n = 0 N 1 r n ψ j , k * ( n )
ψ j , k ( n ) = 1 2 j ψ ( n 2 j k ) .
μ a , b ( λ ) = 100 m 1 ( 0.82 + 16.82 e ( λ 400 nm ) / 80.5 nm ) .
μ s = a ( ( 1 f Rayleigh ) ( λ 500 nm ) b Mie f Rayleigh ( λ 500 nm ) 4 ) .
μ s ( λ ) = 1500 m 1 ( 16.34 + 303.8 e λ / 180.3 nm ) .
n ( λ ) = 1.357 + 6.9 10 3 λ 2 + 7.6 10 8 λ 4 .

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