An automated cervical pre-cancerous diagnostic system

Artificial Intelligence in Medicine

Volumn 42, Issue 1, 2008, Pages 1-11

  Mat Isa, Nor Ashidi ^a   Mashor, Mohd Yusoff ^b   Othman, Nor Hayati ^c  

^a SCHOOL OF CHEMICAL ENGINEERING   (Malaysia)

^b UNIVERSITY MALAYSIA PERLIS   (Malaysia)

^c SCHOOL OF MEDICAL SCIENCES   (Malaysia)

Author keywords

Cervical cancer; Diagnostic system; Feature extraction; Neural network; Pattern analysis; Region growing

Indexed keywords

BIOLOGICAL ORGANS; CELL DEATH; FEATURE EXTRACTION; NEURAL NETWORKS; PIXELS; TUMORS;

CERVICAL CANCER; DIAGNOSTIC SYSTEMS; PATTERN ANALYSIS; REGION GROWING;

DIAGNOSTIC PRODUCTS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATION; CANCER STAGING; CELL NUCLEUS; CELL SIZE; CYTOPLASM; CYTOTECHNOLOGIST; DIAGNOSTIC TEST; HUMAN; PRECANCER; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; SQUAMOUS CELL CARCINOMA; UTERINE CERVIX CANCER; UTERINE CERVIX CARCINOMA IN SITU;

ALGORITHMS; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; IMAGE CYTOMETRY; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; UTERINE CERVICAL NEOPLASMS;

EID: 37649021330     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2007.09.002     Document Type: Article

References (38)

1. Cotran R.S., Kumar V., and Robbins S.L. Robbins: pathologic basis of disease. 5th ed. (1994), W.B. Saunders Company, Philadelphia
2. Breen N., Wagener D.K., Brown M.L., Davis W.W., and Barbash R.B. Progress in cancer screening over a decade: results of cancer screening from the 1987, 1992 and 1998 National Health Interview Surveys. J Natl Cancer Inst 93 22 (2001) 1704-1713
3. Framer P.S. Screening for cancer: progress but more can be done. J Natl Cancer Inst 93 22 (2001) 1676-1677
4. Adami H.O., Ponten J., Sparen P., Bergstrom R., Gustafsson L., and Friberg L.G. Survival trend after invasive cervical cancer diagnosis in Sweden before and after cytologic screening. Cancer 73 1 (1994) 140-147
5. Kuie T.S. Cervical cancer: its causes and prevention (1996), Times Book Int, Singapura
6. Hislop T.G., Band P.R., Deschamps M., Clarke H.F., Smith J.M., and Ng V.T.Y. Cervical cancer screening in Canadian native women: adequacy of the Papanicolaou smear. J Clin Cytol Cytopathol 38 1 (1994) 29-32
7. Othman N.H., Ayub M.C., Aziz W.A.A., Muda M., Wahid R., and Selvarajan S. Pap smears - Is it an effective screening methods for cervical cancer neoplasia? - an experience with 2289 cases. Malaysian J Med Sci 4 1 (1997) 45-50
8. Othman N.H. Cancer of the cervix-from bleak past to bright future (2003), Pustaka Reka Publishing Company, Kelantan, Malaysia
9. MedicineNet. "Pap Smear", http://www.medicinenet.com/pap_smear/page9.html [accessed 1.02.07].
10. Nanda K., MacCrory D.C., Myers E.R., Bastian L.A., Hasselblad V., Hickey J.D., et al. The accuracy of the pappanicolaou test in screening for and follow-up of cervical cytologic abnormalities: a systematic review. Ann Int Med 132 (2000) 810-819
11. Chang K.S., Pavlova I., Marin N., Follen M., and Richards-Kortum R. Fluorescence spectroscopy as a diagnostic tool for detecting cervical pre-cancer. Conference gynecologic oncology, vol. 99, Issue 3, Suppl 1. Elsevier. December (2005) S61-S63
12. Balas C. A novel optical imaging method for the early detection, quantitative grading and mapping of cancerous and precancerous lesions of cervix. IEEE Trans Biomed Eng 48 1 (2001) 96-104
13. Walker D.C., Brown B.H., Hose D.R., and Smallwood R.H. Modelling the electrical impedivity of normal and premalignant cervical tissue. Electr Lett 36 19 (2000) 1603-1604
14. Frable W.J. Cervical screening by neural networks. Cancer Cytopathol 93 3 (2001) 171-172
15. Kok M.R., Boon M.E., Kok P.G.S., Hermans J., Grobbee D.E., and Kok L.P. Less medical intervention after sharp demarcation of grade 1-2 cervical intraepithelial neoplasia smears by neural network screening. Cancer Cytopathol 93 3 (2001) 173-178
16. Li Z., and Najarian K. Automated classification of pap smear tests using neural networks. Proceedings of international joint conference on neural networks, vol. 4. The International Neural Network Society & the IEEE Neural Network Council, Washington, DC (2001) 2899-2901
17. Mitra P., Mitra S., and Pal S.K. Staging of cervical cancer with soft computing. IEEE Trans Biomed Eng 47 7 (2000) 934-940
18. Balasubramaniam R., Rajan S., Doraiswami R., and Stevenson M. A reliable composite classification strategy. Proceedings of IEEE Canadian conference on electrical and computer engineering, vol. 2. IEEE Society. Waterloo, Canada. May (1998) 914-917
19. Ashfaq R., Solares B., and Saboorian M. Detection of endocervical component by Papnet system on negative cervical smears. Diagn. Cytopathol. 15 2 (1996) 121-123
20. Tumer K., Ramanujam N., Ghosh J., and Richards-Kortum R. Ensembles of radial basis function networks for spectroscopic detection of cervical precancer. IEEE Trans Biomed Eng 45 8 (1998) 953-961
21. Bazoon M., Stacey D.A., Cui C., and Harauz G. A hierarchical artificial neural network system for the classification of cervical cells. Proceedings of 1994 IEEE international conference on neural networks, vol. 6. IEEE Neural Networks Council, Orlando, Florida. July (1994) 3525-3529
22. Brouwer R.K. Automatic growing of a Hopfield style neural network for classification of patterns. Proceedings of 5th international conference on image processing and its applications. IEEE Society, Edinburg, United Kingdom, July (1995) 637-641
23. Romberg J, Akram W, Gamiz J. Image segmentation using region growing, http://www.owlnet.rice.edu/∼elec539/Projects97/WDEKnow/introduce.html; 1997 [accessed 10.01.07].
24. Venturi G. Edge and region integration for image segmentation. In: Vernazza G., Venetsanopoulos A.N., and Braccini C. (Eds). Image processing: theory and applications (1993), Elsevier Science Publishers, Amsterdam 181-184
25. Brelstaff G.J. A coarse-to-fine scheme for region growing using statistical tests. In: Vernazza G., Venetsanopoulos A.N., and Braccini C. (Eds). Image processing: theory and applications (1993), Elsevier Science Publishers, Amsterdam 83-86
26. Mat-Isa N.A. Automated detection technique for pap smear images using moving K-means clustering and modified seed based region growing algorithm. Int J Comput Internet Manage 13 3 (2005) 45-59
27. Ngah U.K., Ooi T.H., Sulaiman S.N., and Venkatachalam P.A. Embedded enhancement image processing techniques on a demarcated seed based grown region. In: Omar Z., Pau K.K., Hashim M.A., Taib M.N., Syed-Aman S.M.K., Ng K.H., Haesungcharern A., and Sthaneshwar (Eds). Proceedings of Kuala Lumpur international conference on biomedical engineering. University of Malaya, Kuala Lumpur, Malaysia (2002) 170-172
28. Mashor M.Y. Hybrid training algorithm for RBF network. Int J Comput Internet Manage 8 2 (2000) 50-65
29. Govan A.D.T., MacFarlane P.S., and Callander R. Pathology illustrated. 2nd Ed. (1986), Churchill Livingstone, Edinburgh
30. Mat-Isa, N.A. Early diagnostic system for cervical cancer based on neural networks. PhD thesis. Universiti Sains Malaysia, 2003.
31. Mat-Isa N.A., Ghafar R., Mashor M.Y., Othman N.H., and Madhavan M. Application of the RBF and MLP networks for diagnosis of cervical cancer. In: Wan-Daud W.R., Abdul-Rashid A.K., Hamdan A.R., Yeop-Majlis B., Che-Haron C.H., Mohd-Yusoff K., Sopian K., Jumari K., Mahadi N.M., Abdul-Rahman R., Saari S., Ahmad S., and Abdullah S. (Eds). Proceedings of the 3rd international conference on advances in strategic technologies (ICAST2003). Universiti Kebangsaan Malaysia, Selangor, Malaysia (2003) 849-852
32. Mashor M.Y. Hybrid multilayered perceptron networks. Int J System Sci 31 6 (2000) 771-785
33. Chen S., Cowan C.F.N., Billings S.A., and Grant P.M. A parallel recursive prediction error algorithm for training layered neural networks. Int J Control 51 6 (1990) 1215-1228
34. Devore J.L. Probability and statistics for engineering and the sciences. 5th ed. (2000), Duxbury Press, New York
35. Merriam-Webster. Merriam-Webster's medical dictionary. USA: Merriam-Webster, 1995.
36. Karnon J., Peters J., Platt J., Chilcott J., McGoogan E., and Brewer N. Liquid-based cytology in cervical screening: an updated rapid and systematic review and economic analysis. Health Technol Assess 8 20 (2004). http://www.ncchta.org/fullmono/mon820.pdf [accessed 15.01.07]
37. Trujillo E.V., Sandison D., Ramanujam N., Mitchell M.F., Cantor S., and Kortum R.R. Development of a cost-effective optical system for detection of cervical pre-cancer. Proceedings of the 18th annual international conference of the IEEE engineering in medicine and biology society, vol. 1. IEEE Engineering in Medicine and Biology Society, Amsterdam. November (1997) 191-193
38. Van der Heiden M., Faber G., Ongkiehong L., and Berkhout A.J. A high resolution ultrasonic imaging system for the detection of cervical cancer. Proceedings of the 1996 IEEE symposium on ultrasonics, vol. 2. IEEE Society, San Antonio, Texas, United States of America (1996) 1341-1344