Abstract

Colposcopy is a primary diagnostic method used to detect cancer and precancerous lesions of the uterine cervix. During the examination, the metaplastic and abnormal tissues exhibit different degrees of whiteness (acetowhitening effect) after applying a 3%-5% acetic acid solution. Colposcopists evaluate the color and density of the acetowhite tissue to assess the severity of lesions for the purpose of diagnosis, telemedicine, and annotation. However, the color and illumination of the colposcopic images vary with the light sources, the instruments and camera settings, as well as the clinical environments. This makes assessment of the color information very challenging even for an expert. In terms of developing a Computer-Aided Diagnosis (CAD) system for colposcopy, these variations affect the performance of the feature extraction algorithm for the acetowhite color. Non-uniform illumination from the light source is also an obstacle for detecting acetowhite regions, lesion margins, and anatomic features. There fore, in digital colposcopy, it is critical to map the color appearance of the images taken with different colposcopes into one standard color space with normalized illumination. This paper presents a novel image calibration technique for colposcopic images. First, a specially designed calibration unit is mounted on the colposcope to acquire daily calibration data prior to performing subject examinations. The calibration routine is fast, automated, accurate and reliable. We then use our illumination correction algorithm and a color calibration algorithm to calibrate the exam data. In this paper we describe these techniques and demonstrate their applications in clinical studies.

© 2006 Optical Society of America

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  1. International agency for research in cancer, "Globocan 2002 database," http://www-dep.iarc.fr/.
  2. D. G. Ferris, J. T. Cox, D. M. O'Connor, V. C. Wright, and J. Foerster, Modern Colposcopy. Textbook and Atlas (American Society for Colposcopy and Cervical Pathology, 2004).
  3. R. Reid and P. Scalzi, "Genital warts and cervical cancer. VII. An improved colposcopic index for differentiating benign papillomaviral infections from high-grade cervical intraepithelial neoplasia," Am. J. Obstet. Gynecol. 153,611-618 (1985).
  4. B. L. Craine and E. R. Craine, "Digital imaging colposcopy: basic concepts and applications," Obstet. Gynecol. 82,869-873 (1993).
  5. W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).
  6. M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).
  7. S. Gordon, G. Zimmerman, and H. Greenspan, "Image Segmentation of Uterine Cervix Images for Indexing in PACs," in Proceedings of IEEE 17th Symposium on Computer-based Medical Systems (2004).
  8. H. Lange, "Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix," Image Processing, J. M Fitzpatrick and J. M. Reinhardt, eds., in Proc. SPIE5747, 1004-1017 (2005).
  9. S. Gordon, G. Zimmerman, R. Long, S. Antani, J. Jeronimo, and H. Greenspan, "Content analysis of uterine cervix images: initial steps towards content based indexing and retrieval of cervigrams," Image Processing, J. M. Reinhardt and J. P. Pluim, eds., in Proc. SPIE6144, 1549-1556 (2006).
  10. I. Claude, R. Winzenrieth, P. Pouletaut, and J-C. Boulanger, "Contour Features for Colposcopic Images Classification by Artificial Neural Networks," in Proceedings of International Conference on Pattern Recognition, 771-774 (2002).
  11. V. Van Raad, Z. Xue, and H. Lange, "Lesion margin analysis for automated classification of cervical cancer lesions," Image Processing, J. M. Reinhardt and J. P. Pluim, eds., in Proc. SPIE6144 (2006).
  12. Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
    [CrossRef]
  13. Y. Srinivasan, D. Hernes, B. Tulpule, S. Yang, J. Guo, S. Mitra, S. Yagneswaran, B. Nutter, B. Phillips, R. Long, and D. Ferris, "A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features," Image Processing, J. M. Fitzpatrick and J. M. Reinhardt, eds., in Proc. SPIE5747, 995-1003 (2005).
  14. W. Li and A. Poisson, "Detection and characterization of abnormal vascular patterns in automated cervical image analysis," Lecture Notes in Computer Science : Advances in Visual Computing 4292,627-636 (2006).
  15. S. Yang, J. Guo, P. King, Y. Sriraja, S. Mitra, B. Nutter, D. Ferris, M. Schiffman, J. Jeronimo, and R. Long, "A multi-spectral digital cervigram™ analyzer in the wavelet domain for early detection of cervical cancer," Image Processing, J. M. Fitzpatrick and M. Sonka, eds., in Proc. SPIE5370, 1833-1844 (2004).
  16. H. C. Li, "Regularized color clustering in medical image database," IEEE Trans. Med. Imaging 19,1150-1155 (2000).
    [CrossRef]
  17. H. Palus, Colour spaces (Chapmann and Hall, 1998).
  18. G. Wyszecki and W. S. Styles, Color Science: Concepts and Methods, Quantitative Data and Formulae (New York: Wiley, 1982).
  19. S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
    [CrossRef]
  20. G. Paschos, "Perceptually uniform color spaces for color texture analysis: an empirical evaluation," IEEE Trans. Image Process. 10,932-936 (2001).
    [CrossRef]
  21. S Wolf, is preparing a manuscript to be called "Color Correction Matrix for Digital Still and Video Imaging Systems."
  22. J. M. Benavides, S. Chang, S. Y. Park, R. Richards-Kortum, N. Mackinnon, C. MacAulay, A. Milbourne, A. Malpica, and M. Follen, "Multispectral digital colposcopy for in vivo detection of cervical cancer," Opt. Express 11,1223-1236 (2003).
  23. A. Milbourne, S. Y. Park, J. L. Benedet, D. Miller, T. Ehlen, H. Rhodes, A. Malpica, J. Matisic, NiekirkD. Van, E. N. Atkinson, N. Hadad, N. Mackinnon, C. MacAulay, R. Richards-Kortum, and M. Follen, "Results of a pilot study of multispectral digital colposcopy for the in vivo detection of cervical intraepithelial neoplasia," Gynecol. Oncol. (2005).
  24. <other>. W. Li, STI® Medical Systems, 733 Bishop Street, Honolulu, Hawaii 96813, is preparing a manuscript to be called "Acetowhite color feature extraction algorithm for cervical images."</other>

2006 (1)

W. Li and A. Poisson, "Detection and characterization of abnormal vascular patterns in automated cervical image analysis," Lecture Notes in Computer Science : Advances in Visual Computing 4292,627-636 (2006).

2005 (1)

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

2003 (2)

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

J. M. Benavides, S. Chang, S. Y. Park, R. Richards-Kortum, N. Mackinnon, C. MacAulay, A. Milbourne, A. Malpica, and M. Follen, "Multispectral digital colposcopy for in vivo detection of cervical cancer," Opt. Express 11,1223-1236 (2003).

2001 (1)

G. Paschos, "Perceptually uniform color spaces for color texture analysis: an empirical evaluation," IEEE Trans. Image Process. 10,932-936 (2001).
[CrossRef]

2000 (2)

H. C. Li, "Regularized color clustering in medical image database," IEEE Trans. Med. Imaging 19,1150-1155 (2000).
[CrossRef]

Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
[CrossRef]

1993 (1)

B. L. Craine and E. R. Craine, "Digital imaging colposcopy: basic concepts and applications," Obstet. Gynecol. 82,869-873 (1993).

1992 (1)

M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).

1985 (1)

R. Reid and P. Scalzi, "Genital warts and cervical cancer. VII. An improved colposcopic index for differentiating benign papillomaviral infections from high-grade cervical intraepithelial neoplasia," Am. J. Obstet. Gynecol. 153,611-618 (1985).

Benavides, J. M.

Chang, S.

Craine, B. L.

B. L. Craine and E. R. Craine, "Digital imaging colposcopy: basic concepts and applications," Obstet. Gynecol. 82,869-873 (1993).

Craine, E.

Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
[CrossRef]

Craine, E. R.

B. L. Craine and E. R. Craine, "Digital imaging colposcopy: basic concepts and applications," Obstet. Gynecol. 82,869-873 (1993).

Engel, J.

Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
[CrossRef]

Ferris, D.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Follen, M.

Gu, J.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Hakansson, J.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Hansson, U.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Iakovidis, D. K.

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

Ji, Q.

Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
[CrossRef]

Karkanis, S. A.

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

Karras, D. A.

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

Lange, H.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Li, H. C.

H. C. Li, "Regularized color clustering in medical image database," IEEE Trans. Med. Imaging 19,1150-1155 (2000).
[CrossRef]

Li, W.

W. Li and A. Poisson, "Detection and characterization of abnormal vascular patterns in automated cervical image analysis," Lecture Notes in Computer Science : Advances in Visual Computing 4292,627-636 (2006).

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

MacAulay, C.

Mackinnon, N.

Malpica, A.

Maroulis, D. E.

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

Merkatz, I. R.

M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).

Mikhail, M. S.

M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).

Milbourne, A.

Park, S. Y.

Paschos, G.

G. Paschos, "Perceptually uniform color spaces for color texture analysis: an empirical evaluation," IEEE Trans. Image Process. 10,932-936 (2001).
[CrossRef]

Poisson, A.

W. Li and A. Poisson, "Detection and characterization of abnormal vascular patterns in automated cervical image analysis," Lecture Notes in Computer Science : Advances in Visual Computing 4292,627-636 (2006).

Reid, R.

R. Reid and P. Scalzi, "Genital warts and cervical cancer. VII. An improved colposcopic index for differentiating benign papillomaviral infections from high-grade cervical intraepithelial neoplasia," Am. J. Obstet. Gynecol. 153,611-618 (1985).

Richards-Kortum, R.

Romney, S. L.

M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).

Scalzi, P.

R. Reid and P. Scalzi, "Genital warts and cervical cancer. VII. An improved colposcopic index for differentiating benign papillomaviral infections from high-grade cervical intraepithelial neoplasia," Am. J. Obstet. Gynecol. 153,611-618 (1985).

Tzivras, M.

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

Van Raad, V.

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Am. J. Obstet. Gynecol. (1)

R. Reid and P. Scalzi, "Genital warts and cervical cancer. VII. An improved colposcopic index for differentiating benign papillomaviral infections from high-grade cervical intraepithelial neoplasia," Am. J. Obstet. Gynecol. 153,611-618 (1985).

IEEE Trans. Image Process. (1)

G. Paschos, "Perceptually uniform color spaces for color texture analysis: an empirical evaluation," IEEE Trans. Image Process. 10,932-936 (2001).
[CrossRef]

IEEE Trans. Inf. Technol. Biomed. (1)

S. A. Karkanis, D. K. Iakovidis, D. E. Maroulis, D. A. Karras, and M. Tzivras, "Computer-aided tumor detection in endoscopic video using color wavelet features," IEEE Trans. Inf. Technol. Biomed. 7,141-152 (2003).
[CrossRef]

IEEE Trans. Med. Imaging (2)

H. C. Li, "Regularized color clustering in medical image database," IEEE Trans. Med. Imaging 19,1150-1155 (2000).
[CrossRef]

Q. Ji, J. Engel, and E. Craine, "Texture Analysis for Classification of Cervix Lesions," IEEE Trans. Med. Imaging 19,1144-1149 (2000).
[CrossRef]

Lecture Notes in Computer Science : Advances in Visual Computing (1)

W. Li and A. Poisson, "Detection and characterization of abnormal vascular patterns in automated cervical image analysis," Lecture Notes in Computer Science : Advances in Visual Computing 4292,627-636 (2006).

Lecture Notes in Computer Science, CVBIA (1)

W. Li, V. Van Raad, J. Gu, U. Hansson, J. Hakansson, H. Lange, and D. Ferris, "Computer-aided Diagnosis (CAD) for cervical cancer screening and diagnosis: a new system design in medical image processing," Lecture Notes in Computer Science, CVBIA 2005240-250 (2005).

Obstet. Gynecol. (2)

M. S. Mikhail, I. R. Merkatz, and S. L. Romney, "Clinical usefulness of computerized colposcopy: image analysis and conservative management of mild dysplasia," Obstet. Gynecol. 80,5-8 (1992).

B. L. Craine and E. R. Craine, "Digital imaging colposcopy: basic concepts and applications," Obstet. Gynecol. 82,869-873 (1993).

Opt. Express (1)

Other (14)

H. Palus, Colour spaces (Chapmann and Hall, 1998).

G. Wyszecki and W. S. Styles, Color Science: Concepts and Methods, Quantitative Data and Formulae (New York: Wiley, 1982).

International agency for research in cancer, "Globocan 2002 database," http://www-dep.iarc.fr/.

D. G. Ferris, J. T. Cox, D. M. O'Connor, V. C. Wright, and J. Foerster, Modern Colposcopy. Textbook and Atlas (American Society for Colposcopy and Cervical Pathology, 2004).

S. Gordon, G. Zimmerman, and H. Greenspan, "Image Segmentation of Uterine Cervix Images for Indexing in PACs," in Proceedings of IEEE 17th Symposium on Computer-based Medical Systems (2004).

H. Lange, "Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix," Image Processing, J. M Fitzpatrick and J. M. Reinhardt, eds., in Proc. SPIE5747, 1004-1017 (2005).

S. Gordon, G. Zimmerman, R. Long, S. Antani, J. Jeronimo, and H. Greenspan, "Content analysis of uterine cervix images: initial steps towards content based indexing and retrieval of cervigrams," Image Processing, J. M. Reinhardt and J. P. Pluim, eds., in Proc. SPIE6144, 1549-1556 (2006).

I. Claude, R. Winzenrieth, P. Pouletaut, and J-C. Boulanger, "Contour Features for Colposcopic Images Classification by Artificial Neural Networks," in Proceedings of International Conference on Pattern Recognition, 771-774 (2002).

V. Van Raad, Z. Xue, and H. Lange, "Lesion margin analysis for automated classification of cervical cancer lesions," Image Processing, J. M. Reinhardt and J. P. Pluim, eds., in Proc. SPIE6144 (2006).

S. Yang, J. Guo, P. King, Y. Sriraja, S. Mitra, B. Nutter, D. Ferris, M. Schiffman, J. Jeronimo, and R. Long, "A multi-spectral digital cervigram™ analyzer in the wavelet domain for early detection of cervical cancer," Image Processing, J. M. Fitzpatrick and M. Sonka, eds., in Proc. SPIE5370, 1833-1844 (2004).

Y. Srinivasan, D. Hernes, B. Tulpule, S. Yang, J. Guo, S. Mitra, S. Yagneswaran, B. Nutter, B. Phillips, R. Long, and D. Ferris, "A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features," Image Processing, J. M. Fitzpatrick and J. M. Reinhardt, eds., in Proc. SPIE5747, 995-1003 (2005).

S Wolf, is preparing a manuscript to be called "Color Correction Matrix for Digital Still and Video Imaging Systems."

A. Milbourne, S. Y. Park, J. L. Benedet, D. Miller, T. Ehlen, H. Rhodes, A. Malpica, J. Matisic, NiekirkD. Van, E. N. Atkinson, N. Hadad, N. Mackinnon, C. MacAulay, R. Richards-Kortum, and M. Follen, "Results of a pilot study of multispectral digital colposcopy for the in vivo detection of cervical intraepithelial neoplasia," Gynecol. Oncol. (2005).

<other>. W. Li, STI® Medical Systems, 733 Bishop Street, Honolulu, Hawaii 96813, is preparing a manuscript to be called "Acetowhite color feature extraction algorithm for cervical images."</other>

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