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Mammographic Image and Breast Ultrasound Based Expert System for Breast Diseases

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Book cover Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Abstract

Breast cancer is the most frequently diagnosed malignant disease among women. Due to the rapid advancement in the field of ultrasound and image processing, the usage of ultrasound in conjunction with physical and mammography examination is now preferred in order to obtain a thorough breast examination. This paper focusses on developing an expert system based on mammographic and ultrasound images that may be used by expert and non-expert doctors in the diagnoses of breast diseases . This package consists of a mammographic and breast ultrasound medical expert system which can be used to deduce cases based upon mammograms and breast ultrasound images. The expert system requires the user to answer multiple guided questions before arriving at the final conclusions with the ability to call upon the patients’ images whenever referrals are needed. There also exists an incorporated knowledge base explanations for each question posted and a medical glossary which helps the user to better understand medical terms, questions and answers displayed. Borland C++ Builder was utilized to develop this work so that the package could be integrated with digital image processing modules that may help to accentuate images to aid analyzing procedures.

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References

  1. Parsons, C.A.: Diagnosis of Breast Disease - Imaging, Clinical Features and Pathology. Chapman and Hall, Boca Raton (1983)

    Google Scholar 

  2. Giger, M.: Computing in Science & Engineering (September/October, 1999) (1999)

    Google Scholar 

  3. Giger, M.L.: Computer-Aided Diagnosis of Breast Lesions In Medical Images (September/October, 2000) (2000)

    Google Scholar 

  4. Hou, M., chuang, H., Yang, F., Wang, C., Huang, C., Fan, H., Chuang, C., Wang, J., Sieh, J., Liu, G., Huang, T.: Comparison Of Breast Mammography, Sonography And Physical Examination For Screening Women At High Risk Of Breast Cancer In Taiwan. Ultrasound in Med. & Biol. 28(4), 415–420 (2002)

    Article  Google Scholar 

  5. Cook, H.M., Fox, M.D.: Artificial Intelligence Applied To Mammographic Image Analysis. Electronic Imaging, Boston, pp. 1154–1158 (1987)

    Google Scholar 

  6. Ngah, U.K., Venkatachalam, P.A.: Mammographic Image Integrated Expert System. The International Journal of Computers and Their Applications, USA (December issue), 122–129 (1996)

    Google Scholar 

  7. Kopans, D.B.: Breast Imaging. B. Lippincott Co, Philadelphia, USA (1989)

    Google Scholar 

  8. Mat-Isa, N.A., Mashor, M.Y., Othman, N.H.: Classification of Cervical Cancer Cells Using HMLP Network with Confidence Percentage and Confidence Level Analysis. The International Journal of the Computer, the Internet and Management 11(1), 17–29 (2003)

    Google Scholar 

  9. http://www.uchsc.edu/uh/radiology/bust_tf/index.html

  10. Reisdorph, K.: Teach Yourself Borland C++ Builder 3 In 21 Days. Sams Publishing (1998)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Ngah, U.K., Ping, C.C., Aziz, S.A. (2004). Mammographic Image and Breast Ultrasound Based Expert System for Breast Diseases. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_83

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  • DOI: https://doi.org/10.1007/978-3-540-30132-5_83

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23318-3

  • Online ISBN: 978-3-540-30132-5

  • eBook Packages: Springer Book Archive

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