Abstract

An artificial neural network (ANN) has been used in various clinical research for the prediction and classification of data in cancer disease. Previous research in this direction focused on the correlation between various input parameters such as age, antigen, and size of tumor growth. Recently, laser-induced autofluorescence (LIAF) techniques have been shown to be a useful noninvasive early diagnostic tool for various cancer diseases. We report on a successful application of ANN to in vitro LIAF spectra. We show that classification of tumor samples with ANN can be done with high sensitivity, specificity, and accuracy. Thus a combination of LIAF techniques and ANN can provide a robust method for clinical diagnosis.

© 2005 Optical Society of America

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  1. For the latest U.S. statistics, see http://seer.cancer.gov ; for Canadian statistics, see http://www.cancer.ca ; for Australian statistics, see http://www.nswcc.org.au/ . For statistics on China and Japan, see World Health Statistics Annual (World Health Organization, 1996).
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    [CrossRef] [PubMed]
  3. V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
    [CrossRef] [PubMed]
  4. G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
    [CrossRef]
  5. J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
    [CrossRef] [PubMed]
  6. Z. Ge, K. T. Schomacker, N. S. Nishioka, “Identification of colonic dysplasia by diffuse spectroscopy and pattern recognition techniques,” Appl. Spectrosc. 52, 833–839 (1998).
    [CrossRef]
  7. E. Sevick-Muraca, R. Richards-Kortum, “Quantitative optical spectroscopy for tissue diagnosis,” Am. Rev. Phys. Chem. 47, 555–606 (1996).
    [CrossRef]
  8. G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
    [CrossRef] [PubMed]
  9. H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
    [CrossRef] [PubMed]
  10. N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
    [CrossRef] [PubMed]
  11. K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
    [CrossRef]
  12. T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
    [CrossRef] [PubMed]
  13. M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
    [CrossRef] [PubMed]
  14. S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
    [CrossRef]
  15. S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).
  16. R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
    [CrossRef]
  17. H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
    [CrossRef]
  18. H. A. Abbass, “An evolutionary artificial neural networks approach for breast cancer diagnosis,” Artif. Intell. Med. 25, 265–281 (2002).
    [CrossRef] [PubMed]
  19. E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
    [CrossRef]
  20. C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
    [CrossRef] [PubMed]
  21. S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
    [CrossRef] [PubMed]
  22. C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
    [PubMed]
  23. B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
    [CrossRef] [PubMed]
  24. P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
    [CrossRef] [PubMed]
  25. C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
    [CrossRef]
  26. R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
    [CrossRef] [PubMed]
  27. R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
    [CrossRef]
  28. P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).
  29. P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).
  30. T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).
  31. W. S. McCulloch, W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” Bull. Math. Biophys. 5, 115–133 (1943).
    [CrossRef]
  32. V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
    [CrossRef] [PubMed]

2004

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

2003

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

2002

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

H. A. Abbass, “An evolutionary artificial neural networks approach for breast cancer diagnosis,” Artif. Intell. Med. 25, 265–281 (2002).
[CrossRef] [PubMed]

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

2000

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

1999

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
[CrossRef]

1998

H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
[CrossRef]

M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
[CrossRef] [PubMed]

G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
[CrossRef] [PubMed]

H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
[CrossRef] [PubMed]

Z. Ge, K. T. Schomacker, N. S. Nishioka, “Identification of colonic dysplasia by diffuse spectroscopy and pattern recognition techniques,” Appl. Spectrosc. 52, 833–839 (1998).
[CrossRef]

1996

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

E. Sevick-Muraca, R. Richards-Kortum, “Quantitative optical spectroscopy for tissue diagnosis,” Am. Rev. Phys. Chem. 47, 555–606 (1996).
[CrossRef]

1992

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

1989

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

1984

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

1983

T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).

1943

W. S. McCulloch, W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” Bull. Math. Biophys. 5, 115–133 (1943).
[CrossRef]

Abbass, H. A.

H. A. Abbass, “An evolutionary artificial neural networks approach for breast cancer diagnosis,” Artif. Intell. Med. 25, 265–281 (2002).
[CrossRef] [PubMed]

Alfano, M. A.

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

Alfano, R. R.

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

Arendt, J. T.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Argov, S.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Atkinson, N.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Backman, V.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

Badizadegan, K.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Bahaian, R. J.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Bamber, J. C.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Bansal, G.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Baumgartner, R.

H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
[CrossRef] [PubMed]

Beetner, D. G.

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

Bganzoli, E.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

Biehl, M.

T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).

Bigio, I. J.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

Bonner, R. F.

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

Boracchi, P.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

Boyer, J.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

Brawer, M. K.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Brux, B.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Cammann, H.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Chia, K.-S.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Chia, T. C.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

Cline, R.

H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
[CrossRef]

Cohen, P.

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

Compton, J.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Coradini, D.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

Crawford, D. C.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Crawford, J. M.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

DaCosta, R. S.

R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
[CrossRef]

Dasari, R. R.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Deutsch, T.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Diamandis, E. P.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Diong, C. H.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

Djavan, B.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Du, W.-B.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Dua, R.

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

Dunn, S. M.

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

Feld, M.

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

Feld, M. S.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

Fitzmaurice, M.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

Fleischer, D. E.

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

Flotte, T.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Follen-Mitchell, M.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Frisoli, J.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Fu, S.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

Garzia Daidone, M.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

Ge, Z.

Goldstein, J.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Gurjar, R.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Guterman, H.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Hauptmann, S.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Itzkan, I.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

Johnson, T. M.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

Jung, K.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Kabani, S.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Kalra, P.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Kline, E.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Krishnan, S. M.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

Kristiansen, G.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Kundel, H. L.

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

Kwek, L. C.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

Lacey, J.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

Lee, H. P.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Lein, M.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Leon, M. B.

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

Levin, H. S.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Loening, S. A.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

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R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
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H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
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N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Malpica, A.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Manharan, R.

Marberger, M.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Marcon, N. E.

R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
[CrossRef]

Marubini, E.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

McCulloch, W. S.

W. S. McCulloch, W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” Bull. Math. Biophys. 5, 115–133 (1943).
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McGillican, T.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Mello-Thoms, C.

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

Mordechai, S.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Mortimer, P. S.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Mourant, J. R.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

Müller, M. G.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Mycek, M. A.

M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
[CrossRef] [PubMed]

Niederberger, C. S.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Nishioka, N.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Nishioka, N. S.

M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
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Z. Ge, K. T. Schomacker, N. S. Nishioka, “Identification of colonic dysplasia by diffuse spectroscopy and pattern recognition techniques,” Appl. Spectrosc. 52, 833–839 (1998).
[CrossRef]

Nodine, C. F.

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

Ott, R. J.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Partin, A. W.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Patterson, R.

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

Perelman, L. T.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

Pitts, W.

W. S. McCulloch, W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” Bull. Math. Biophys. 5, 115–133 (1943).
[CrossRef]

Ramanujam, N.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Ramesh, J.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
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T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).

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B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Richards-Kortum, R.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
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E. Sevick-Muraca, R. Richards-Kortum, “Quantitative optical spectroscopy for tissue diagnosis,” Am. Rev. Phys. Chem. 47, 555–606 (1996).
[CrossRef]

Richter, J.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Ross, L. S.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Rudolph, B.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Salman, A.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Sankaramarayanan, R.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Sankila, R.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Schnorr, D.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Schomacker, K.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Schomacker, K. T.

M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
[CrossRef] [PubMed]

Z. Ge, K. T. Schomacker, N. S. Nishioka, “Identification of colonic dysplasia by diffuse spectroscopy and pattern recognition techniques,” Appl. Spectrosc. 52, 833–839 (1998).
[CrossRef]

Seiler, M.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Seitz, C.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Semjonow, A.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Seow, A.

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

Seow Choen, F.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

Sevick-Muraca, E.

E. Sevick-Muraca, R. Richards-Kortum, “Quantitative optical spectroscopy for tissue diagnosis,” Am. Rev. Phys. Chem. 47, 555–606 (1996).
[CrossRef]

Shapshay, S.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Sinelnikov, I.

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

Sinha, P.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Sinia, P.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Snow, P.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Sroka, R.

H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
[CrossRef] [PubMed]

Staerkel, G.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Star, W. M.

G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
[CrossRef] [PubMed]

Stephan, C.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Stephen, C.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Stepp, H.

H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
[CrossRef] [PubMed]

Stoecker, W. V.

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

Tang, C. L.

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

Tata, D. B.

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

Thomsen, S.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Togam, J.

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Tomashefsky, P.

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

Valdez, T.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Van Dam, J.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

Vogel, B.

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

Wagnieres, G. A.

G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
[CrossRef] [PubMed]

Wallace, M. B.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Wallace, V. P.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Wang, T. D.

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

Wang, Y.

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

Watkin, T. L. H.

T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).

Weiss, A.

H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
[CrossRef]

Wilson, B. C.

R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
[CrossRef]

G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
[CrossRef] [PubMed]

Wright, T.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

Wunsch, D. C.

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

Wymenga, L. F. A.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Yakshe, P. N.

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

Zeng, H.

H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
[CrossRef]

Zhang, Q.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Zlotta, A.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Zonios, G.

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

G. Zonios, L. T. Perelman, V. Backman, R. Manharan, M. Fitzmaurice, J. Van Dam, M. S. Feld, “Diffuse reflectance spectroscopy of human adenomatous colon polyp in vivo,” Appl. Opt. 38, 6628–6637 (1999).
[CrossRef]

Am. J. Gastroenterol.

P. N. Yakshe, R. F. Bonner, R. Patterson, M. B. Leon, D. E. Fleischer, “Laser induced fluorescence spectroscopy (LIFS): can it be used in the diagnosis and treatment of colonic malignancy?,” Am. J. Gastroenterol. 84, 1199 (1989).

Am. Rev. Phys. Chem.

E. Sevick-Muraca, R. Richards-Kortum, “Quantitative optical spectroscopy for tissue diagnosis,” Am. Rev. Phys. Chem. 47, 555–606 (1996).
[CrossRef]

Ann. Oncol.

E. Bganzoli, P. Boracchi, D. Coradini, M. Garzia Daidone, E. Marubini, “Prognosis in node-negative primary breast cancer: a neural network analysis of risk profiles using routinely assessed factors,” Ann. Oncol. 14, 1484–1493 (2003).
[CrossRef]

Appl. Opt.

Appl. Spectrosc.

Artif. Intell. Med.

H. A. Abbass, “An evolutionary artificial neural networks approach for breast cancer diagnosis,” Artif. Intell. Med. 25, 265–281 (2002).
[CrossRef] [PubMed]

Bioimaging

H. Zeng, A. Weiss, R. Cline, C. MacAulay, “Real-time endoscopic fluorescence imaging for early cancer detection in the gastrointestinal tract,” Bioimaging 6, 151–165 (1998).
[CrossRef]

Bull. Math. Biophys.

W. S. McCulloch, W. Pitts, “A logical calculus of the ideas immanent in nervous activity,” Bull. Math. Biophys. 5, 115–133 (1943).
[CrossRef]

Cancer

P. Kalra, J. Togam, G. Bansal, A. W. Partin, M. K. Brawer, R. J. Bahaian, L. S. Ross, C. S. Niederberger, “A neurocomputational model for prostate carcinoma detection,” Cancer 98, 1849–1854 (2003).
[CrossRef] [PubMed]

Clin. Chem.

C. Stephan, H. Cammann, A. Semjonow, E. P. Diamandis, L. F. A. Wymenga, M. Lein, P. Sinha, S. A. Loening, K. Jung, “Multicenter evaluation of an artificial Neural Network to increase the prostate cancer detection rate and reduce unnecessary biopsies,” Clin. Chem. 48, 1279–1287 (2002).
[PubMed]

Dig. Endosc.

R. S. DaCosta, B. C. Wilson, N. E. Marcon, “Recent advances in light induced fluorescence endoscopy in the GI tract (invited review),” Dig. Endosc. 11, 108–118 (1999).
[CrossRef]

Endoscopy

H. Stepp, R. Sroka, R. Baumgartner, “Fluorescence endoscopy of gastrointestinal diseases: basic principles, techniques and clinical experiences,” Endoscopy 30, 379–386 (1998).
[CrossRef] [PubMed]

Gastrointest. Endosc.

T. D. Wang, J. M. Crawford, M. Feld, Y. Wang, I. Itzkan, J. Van Dam, “In vivo identification of colonic dysplasia using fluorescence endoscopic imaging,” Gastrointest. Endosc. 49, 447–455 (1999).
[CrossRef] [PubMed]

M. A. Mycek, K. T. Schomacker, N. S. Nishioka, “Colonic polyp differentiation using time resolved autofluorescence spectroscopy,” Gastrointest. Endosc. 48, 390–394 (1998).
[CrossRef] [PubMed]

P. N. Yakshe, R. F. Bonner, P. Cohen, M. B. Leon, D. E. Fleischer, “Laser-induced fluorescence spectroscopy may distinguish colon cancer from normal mucosa,” Gastrointest. Endosc. 35, 184 (1989).

IEEE Quantum Electron.

R. R. Alfano, D. B. Tata, P. Tomashefsky, F. W. Longo, M. A. Alfano, “Laser induced fluorescence spectroscopy from native cancerous and normal tissue,” IEEE Quantum Electron. 20, 1507–1511 (1984).
[CrossRef]

IEEE Trans. Biomed. Eng.

R. Dua, D. G. Beetner, W. V. Stoecker, D. C. Wunsch, “Detection of basal cell carcinoma using electrical impedance and neural network,” IEEE Trans. Biomed. Eng. 51, 66–71 (2004).
[CrossRef] [PubMed]

IEEE Trans. Med. Imaging

C. Mello-Thoms, S. M. Dunn, C. F. Nodine, H. L. Kundel, “The perception of breast cancers—a spatial frequency analysis of what differentiates missed from reported cancers,” IEEE Trans. Med. Imaging 22, 1297–1306 (2003).
[CrossRef] [PubMed]

Int. J. Cancer

C. Stephen, K. Jung, H. Cammann, B. Vogel, B. Brux, G. Kristiansen, B. Rudolph, S. Hauptmann, M. Lein, D. Schnorr, P. Sinia, S. A. Loening, “An artificial neural network considerably improves the diagnostic power of percent free prostate-specific antigen in prostate cancer diagnosis,” Int. J. Cancer 99, 466–473 (2002).
[CrossRef]

W.-B. Du, K.-S. Chia, R. Sankaramarayanan, R. Sankila, A. Seow, H. P. Lee, “Population-based survival analysis of colorectal cancer patients in Singapore, 1968-1992,” Int. J. Cancer 99, 460–465 (2002).
[CrossRef] [PubMed]

J. Biomed. Opt.

J. R. Mourant, I. J. Bigio, J. Boyer, T. M. Johnson, J. Lacey, “Elastic scattering spectroscopy as a diagnostic for differentiating pathologies in the gastrointestinal tract: preliminary testing,” J. Biomed. Opt. 1, 192–199 (1996).
[CrossRef] [PubMed]

S. Argov, J. Ramesh, A. Salman, I. Sinelnikov, J. Goldstein, H. Guterman, S. Mordechai, “Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients,” J. Biomed. Opt. 7, 248–254 (2002).
[CrossRef] [PubMed]

J. Clin. Oncol.

B. Djavan, M. Remzi, A. Zlotta, C. Seitz, P. Snow, M. Marberger, “Novel artificial neural network for early detection of prostate cancer,” J. Clin. Oncol. 20, 921–929 (2002).
[CrossRef] [PubMed]

Lasers Surg. Med.

K. Schomacker, J. Frisoli, J. Compton, T. Flotte, J. Richter, N. Nishioka, T. Deutsch, “Ultraviolet laser induced fluorescence of colonic tissue: basic biology and diagnostic potential,” Lasers Surg. Med. 12, 63–78 (1992).
[CrossRef]

Nature

V. Backman, M. B. Wallace, L. T. Perelman, J. T. Arendt, R. Gurjar, M. G. Müller, Q. Zhang, G. Zonios, E. Kline, T. McGillican, S. Shapshay, T. Valdez, K. Badizadegan, J. M. Crawford, M. Fitzmaurice, S. Kabani, H. S. Levin, M. Seiler, R. R. Dasari, I. Itzkan, J. Van Dam, M. S. Feld, “Detection of preinvasive cancer cells,” Nature 406, 35–36 (2000).
[CrossRef] [PubMed]

Photochem. Photobiol.

N. Ramanujam, M. Follen-Mitchell, A. Mahadevan-Jansen, S. Thomsen, G. Staerkel, A. Malpica, T. Wright, N. Atkinson, R. Richards-Kortum, “Cervical precancer detection using multivariate statistical algorithm based on laser fluorescence spectra at multiple excitation wavelengths,” Photochem. Photobiol. 64, 720–735 (1996).
[CrossRef] [PubMed]

G. A. Wagnieres, W. M. Star, B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochem. Photobiol. 68, 603–632 (1998).
[CrossRef] [PubMed]

Phys. Med. Biol.

V. P. Wallace, J. C. Bamber, D. C. Crawford, R. J. Ott, P. S. Mortimer, “Classification of reflectance spectra from pigmented skin lesions, a comparison of multivariate discriminant analysis and artificial neural network,” Phys. Med. Biol. 45, 2859–2871 (2000).
[CrossRef] [PubMed]

Rev. Mod. Phys.

T. L. H. Watkin, A. Rau, M. Biehl, “The statistical mechanics of learning a rule,” Rev. Mod. Phys. 65, 488–556 (1983).

Other

For the latest U.S. statistics, see http://seer.cancer.gov ; for Canadian statistics, see http://www.cancer.ca ; for Australian statistics, see http://www.nswcc.org.au/ . For statistics on China and Japan, see World Health Statistics Annual (World Health Organization, 1996).

S. Fu, T. C. Chia, C. H. Diong, C. L. Tang, F. Seow Choen, “Changes in in-vivo autofluorescence spectra at different periods in rat colorectal tumor progression,” in Diagnostic Optical Spectroscopy in Biomedicine, T. G. Papazoglou, G. A. Wagnieres, eds., Proc. SPIE4432, 118–123 (2001).
[CrossRef]

S. Fu, T. C. Chia, C. L. Tang, C. H. Diong, L. C. Kwek, F. Seow Choen, S. M. Krishnan, “Studies of laser induced autofluorescence intensity ratio in human colorectal cancer diagnosis,” Asian J. Phys. (to be published).

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Figures (4)

Fig. 1
Fig. 1

Schematic diagram of a simple perceptron with a step function as the output function. The output is a step function that yields either 0 or 1 depending on the weighted sum of the 566 input values.

Fig. 2
Fig. 2

Schematic diagram of the equipment for the collection of LIAF spectra. The probe consisted of an array of six 300 m core, 0.3 NA collection fibers surrounding a single 300 m, 0.3 NA excitation fiber terminating at a 1 mm diameter tip of the probe.

Fig. 3
Fig. 3

Plots of the intensity versus wavelength for two typical curves: A, normal tissue; B, tumor tissue. Notice that there is a distinct peak in the tumor tissues at the wavelength around 630 nm.

Fig. 4
Fig. 4

Weights of the perceptron ANN corresponding to the 566 input values between the wavelengths of 499.98 and 700.7 nm. Each point is plotted with its standard error.

Tables (2)

Tables Icon

Table 1 Sensitivity, Specificity, and Accuracy for Ten Random Simulations of the Data Set

Tables Icon

Table 2 Cases of True Positive, True Negative, False Positive, and False Negative Giving a Sensitivity and Specificity of 99.2%a and 99.4%b

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