Abstract

We discuss the use of a noninvasive in vivo optical technique, diffuse reflectance spectroscopic imaging with oblique incidence, to distinguish between benign and cancer-prone skin lesions. Various image features were examined to classify the images from lesions into benign and cancerous categories. Two groups of lesions were processed separately: Group 1 includes keratoses, warts versus carcinomas; and group 2 includes common nevi versus dysplastic nevi. A region search algorithm was developed to extract both one- and two-dimensional spectral information. A bootstrap-based Bayes classifier was used for classification. A computer-assisted tool was then devised to act as an electronic second opinion to the dermatologist. Our approach generated only one false-positive misclassification out of 23 cases collected for group 1 and two misclassifications out of 34 cases collected for group 2 under the worst estimation condition.

© 2002 Optical Society of America

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  19. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, Boston, 1990).
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    [CrossRef]
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2000 (3)

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

S. P. Stratton, R. T. Dorr, D. S. Alberts, “The state-of-the-art in chemoprevention of skin cancer,” Eur. J. Cancer 36, 1292–1297 (2000).
[CrossRef] [PubMed]

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

1999 (1)

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

1998 (3)

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

R. W. Demetrius, H. W. Randle, “High-risk nonmelanoma skin cancers,” Dermatol. Surg. 24, 1272–1292 (1998).
[CrossRef] [PubMed]

G. Marquez, L.-H. Wang, S.-P. Lin, J. A. Schwartz, S. L. Thomsen, “Anisotropy in the absorption and scattering spectra of chicken breast tissue,” Appl. Opt. 37, 798–805 (1998).
[CrossRef]

1997 (1)

1995 (1)

A. Baraldi, F. Parmiggiani, “An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters,” IEEE Trans. Geosci. Remote Sens.293–304 33, (1995).
[CrossRef]

1986 (1)

B. Efron, R. Tibshirani, “Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy,” Stat. Sci. 1, 54–75 (1986).
[CrossRef]

Alberts, D. S.

S. P. Stratton, R. T. Dorr, D. S. Alberts, “The state-of-the-art in chemoprevention of skin cancer,” Eur. J. Cancer 36, 1292–1297 (2000).
[CrossRef] [PubMed]

Backman, V.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Badizadegan, K.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Bamber, J. C.

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Baraldi, A.

A. Baraldi, F. Parmiggiani, “An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters,” IEEE Trans. Geosci. Remote Sens.293–304 33, (1995).
[CrossRef]

Bolden, S.

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

Bunn, H. F.

H. F. Bunn, B. G. Forget, Hemoglobin: Molecular, Genetic and Clinical Aspects (Saunders, Philadelphia, Pa., 1986).

Cooney, K. M.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Coté, G. L.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Crawford, D. C.

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Dalton, K. J.

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

Dance, C. R.

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

DeLeo, J. M.

J. M. DeLeo, “Receiver operating characteristic laboratory (ROCLAB): software for developing decision strategies that account for uncertainty,” in Proceedings of the Second International Symposium on Uncertainty Modeling and Analysis, B. M. Ayyub, ed. (IEEE Computer Society Press, Los Alamitos, Calif., 1993), pp. 318–325.

Demetrius, R. W.

R. W. Demetrius, H. W. Randle, “High-risk nonmelanoma skin cancers,” Dermatol. Surg. 24, 1272–1292 (1998).
[CrossRef] [PubMed]

Desari, R. R.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Djuric, P. M.

P. M. Djurić, “Using the bootstrap to select models,” in IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE Computer Society Press, Los Alamitos, Calif., 1997), pp. 3729–3732.

Dorr, R. T.

S. P. Stratton, R. T. Dorr, D. S. Alberts, “The state-of-the-art in chemoprevention of skin cancer,” Eur. J. Cancer 36, 1292–1297 (2000).
[CrossRef] [PubMed]

Efron, B.

B. Efron, R. Tibshirani, “Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy,” Stat. Sci. 1, 54–75 (1986).
[CrossRef]

Feld, M. S.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Forget, B. G.

H. F. Bunn, B. G. Forget, Hemoglobin: Molecular, Genetic and Clinical Aspects (Saunders, Philadelphia, Pa., 1986).

Fukunaga, K.

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, Boston, 1990).

Ghosh, J.

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

Gossage, K. W.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Greenlee, R. T.

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

Gurjar, R.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Itzkan, I.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Koutroumbas, K.

S. Theodoridis, K. Koutroumbas, Pattern Recognition (Academic, San Diego, Calif, 1999).

Lin, S.-P.

Lovell, D. R.

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

Marquez, G.

McShane, M. J.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Mehrübeoglu, M.

M. Mehrübeoğlu, “Diffuse reflectance imaging modalities for characterization of highly scattering turbid media,” Ph.D. dissertation (Texas AM University, College Station, Tex., 2000), pp. 38–142.

Mortimer, P. S.

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Motamedi, M.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Murray, T.

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

Niranjan, M.

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

Ott, R. J.

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Parmiggiani, F.

A. Baraldi, F. Parmiggiani, “An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters,” IEEE Trans. Geosci. Remote Sens.293–304 33, (1995).
[CrossRef]

Perelman, L. T.

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

Prager, R. W.

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

Ramanujam, N.

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

Randle, H. W.

R. W. Demetrius, H. W. Randle, “High-risk nonmelanoma skin cancers,” Dermatol. Surg. 24, 1272–1292 (1998).
[CrossRef] [PubMed]

Richards-Kortum, R.

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

Riech, M.

J. Röning, M. Riech, “Registration of nevi in successive skin images for early detection of melanoma,” in Proceedings of the Fourteenth International Conference on Pattern Recognition, A. K. Jain, S. Venkatesh, B. C. Lovell, eds. (IEEE Computer Society Press, Los Alamitos, Calif., 1998), Vol. 1, pp. 352–357.

Röning, J.

J. Röning, M. Riech, “Registration of nevi in successive skin images for early detection of melanoma,” in Proceedings of the Fourteenth International Conference on Pattern Recognition, A. K. Jain, S. Venkatesh, B. C. Lovell, eds. (IEEE Computer Society Press, Los Alamitos, Calif., 1998), Vol. 1, pp. 352–357.

Schwartz, J. A.

Stratton, S. P.

S. P. Stratton, R. T. Dorr, D. S. Alberts, “The state-of-the-art in chemoprevention of skin cancer,” Eur. J. Cancer 36, 1292–1297 (2000).
[CrossRef] [PubMed]

Theodoridis, S.

S. Theodoridis, K. Koutroumbas, Pattern Recognition (Academic, San Diego, Calif, 1999).

Thomsen, S. L.

Tibshirani, R.

B. Efron, R. Tibshirani, “Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy,” Stat. Sci. 1, 54–75 (1986).
[CrossRef]

Tumer, K.

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

van der Breggen, E. W. J.

K. M. Cooney, K. W. Gossage, M. J. McShane, E. W. J. van der Breggen, M. Motamedi, G. L. Coté, “Development of an optical system for the detection of oral cancer using near-infrared spectroscopy,” in Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, H. K. Chang, Y. T. Zhang, eds. (Institute of Electrical and Electronics Engineers, Piscataway, N.J., 1998), Vol. 2, pp. 906–909.

Vaughan, R. A.

R. A. Vaughan, Pattern Recognition and Image Processing in Physics: Proceedings of the Thirty-Seventh Scottish Universities Summer School in Physics (Scottish Universities Summer School in Physics and Adam Hilger, Bristol, UK, 1991).

Wallace, V. P.

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Wang, L.-H.

Wingo, P. A.

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

Appl. Opt. (1)

CA Cancer J. Clin. (1)

R. T. Greenlee, T. Murray, S. Bolden, P. A. Wingo, “Cancer statistics, 2000,” CA Cancer J. Clin. 50, 7–33 (2000).
[CrossRef] [PubMed]

Dermatol. Surg. (1)

R. W. Demetrius, H. W. Randle, “High-risk nonmelanoma skin cancers,” Dermatol. Surg. 24, 1272–1292 (1998).
[CrossRef] [PubMed]

Eur. J. Cancer (1)

S. P. Stratton, R. T. Dorr, D. S. Alberts, “The state-of-the-art in chemoprevention of skin cancer,” Eur. J. Cancer 36, 1292–1297 (2000).
[CrossRef] [PubMed]

IEEE J. Sel. Top. Quantum Electron. (1)

V. Backman, R. Gurjar, K. Badizadegan, I. Itzkan, R. R. Desari, L. T. Perelman, M. S. Feld, “Polarized light scattering spectroscopy for quantitative measurement of epithelial cellular structures in situ,” IEEE J. Sel. Top. Quantum Electron. 5, 1019–1926 (1999).
[CrossRef]

IEEE Trans. Biomed. Eng. (1)

K. Tumer, N. Ramanujam, J. Ghosh, R. Richards-Kortum, “Ensembles of radial basis function networks for spectroscopic detection of cervical precancer,” IEEE Trans. Biomed. Eng. 45, 953–961 (1998).
[CrossRef] [PubMed]

IEEE Trans. Geosci. Remote Sens. (1)

A. Baraldi, F. Parmiggiani, “An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters,” IEEE Trans. Geosci. Remote Sens.293–304 33, (1995).
[CrossRef]

Opt. Express (1)

Phys. Med. Biol. (1)

V. P. Wallace, D. C. Crawford, P. S. Mortimer, R. J. Ott, J. C. Bamber, “Spectrophotometric assessment of pigmented skin lesions: methods and feature selection for evaluation of diagnostic performance,” Phys. Med. Biol. 45, 735–751 (2000).
[CrossRef] [PubMed]

Stat. Sci. (1)

B. Efron, R. Tibshirani, “Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy,” Stat. Sci. 1, 54–75 (1986).
[CrossRef]

Other (13)

P. M. Djurić, “Using the bootstrap to select models,” in IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE Computer Society Press, Los Alamitos, Calif., 1997), pp. 3729–3732.

H. F. Bunn, B. G. Forget, Hemoglobin: Molecular, Genetic and Clinical Aspects (Saunders, Philadelphia, Pa., 1986).

Statistical Abstract of the United States 1998 (U.S. Census Bureau, Washington, D.C., 1998), Table 239, p. 152.

R. A. Vaughan, Pattern Recognition and Image Processing in Physics: Proceedings of the Thirty-Seventh Scottish Universities Summer School in Physics (Scottish Universities Summer School in Physics and Adam Hilger, Bristol, UK, 1991).

D. R. Lovell, C. R. Dance, M. Niranjan, R. W. Prager, K. J. Dalton, “Using upper bounds on attainable discrimination to select discrete valued features,” in Neural Networks for Signal Processing VI: Proceedings of the 1996 IEEE Signal Processing Society Workshop, S. Usui, ed. (Institute of Electrical and Electronics Engineers, New York, 1996), pp. 233–242.
[CrossRef]

J. M. DeLeo, “Receiver operating characteristic laboratory (ROCLAB): software for developing decision strategies that account for uncertainty,” in Proceedings of the Second International Symposium on Uncertainty Modeling and Analysis, B. M. Ayyub, ed. (IEEE Computer Society Press, Los Alamitos, Calif., 1993), pp. 318–325.

M. Mehrübeoğlu, “Diffuse reflectance imaging modalities for characterization of highly scattering turbid media,” Ph.D. dissertation (Texas AM University, College Station, Tex., 2000), pp. 38–142.

S. Theodoridis, K. Koutroumbas, Pattern Recognition (Academic, San Diego, Calif, 1999).

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, Boston, 1990).

Advances in Optical Imaging and Photon Migration, C. Chang-Hasnain, ed., Vol. 15 of OSA Trends in Optics and Photonics Series (Optical Society of America, Washington, D.C., 1998).

J. Röning, M. Riech, “Registration of nevi in successive skin images for early detection of melanoma,” in Proceedings of the Fourteenth International Conference on Pattern Recognition, A. K. Jain, S. Venkatesh, B. C. Lovell, eds. (IEEE Computer Society Press, Los Alamitos, Calif., 1998), Vol. 1, pp. 352–357.

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Figures (9)

Fig. 1
Fig. 1

Optical probe for light transmission. The source fiber transmits the white light onto the skin surface. The diffusely reflected light off the skin surface is collected by a series of 13 optical collection fibers.

Fig. 2
Fig. 2

DRSI system. The spectral information from the diffusely reflected light off the skin surface is transmitted to the CCD camera system via the probe and the imaging spectrograph.

Fig. 3
Fig. 3

Sample image. Horizontal axis, location of fibers. Vertical axis, wavelength at which the light was collected. Different shades of gray in the image represent the relative intensity of the received light. (Correct aspect ratio is not shown, for visual clarity.)

Fig. 4
Fig. 4

Sample intensity-scaled single-fiber spectra from benign (left) and cancerous (right) skin lesions in group 1.

Fig. 5
Fig. 5

Sample intensity-scaled single-fiber spectra from benign or common nevi (left), and intermediate or dysplastic nevi (right) lesions in group 2.

Fig. 6
Fig. 6

Schematic diagram of the region scanned by the RSA. The width of the window corresponding to fiber number was kept at 9 pixels. The length, L i , and location of the window were varied to find the optimum region and width of region for a given feature.

Fig. 7
Fig. 7

Scatter plot for the conditioned classifier input feature for group 1.

Fig. 8
Fig. 8

Scatter plot for the conditioned classifier input feature for group 2.

Fig. 9
Fig. 9

ROC curve for the features displayed in Figs. 7 and 8.

Tables (7)

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Table 1 List of Examined Featuresa

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Table 2 List of Introduced Featuresa

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Table 3 Effective Features for Group 1 from Which the Classifier Features are Selected

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Table 4 Effective Features for Group 2 from Which the Classifier Features Are Selected

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Table 5 Performance of the Bootstrap-Based Classifier Designed for Lesions in Group 1a

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Table 6 Performance of the Bootstrap-Based Classifier Designed for Lesions in Group 2a

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Table 7 Summary of Procedure to Classify Unknown Lesions

Equations (4)

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Fbc=|μb-μc|/σb2+σc21/2,
J=SW-1SB.
x*=λ1-1/2v1Tx-μ,
μk=1Bb=1B θkb,

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