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Neural Network Based Algorithms for Diagnosis and Classification of Breast Cancer Tumor

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Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

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Abstract

This paper outlines an approach for applying acquiring numerical breast cancer image data and diagnosis using neural network algorithm in a way that is easy to classify between benign and malignance. This paper is an extended work related to our previous work [1]. In our previous work we used k-means algorithm to detect and diagnosis breast cancer tumor’s region. However, to find the better results from the algorithm we need to add more numerical parameters of the breast cancer image and this algorithm has limited usage when applied with more number of parameters. Even if the cancer tumor is abnormal it was quite difficult to distinguish among those tumors. This paper summarizes the different comparative study of neural network algorithms to get the best classification of the breast cancer and explains how to acquire more numerical parameters from the breast cancer image data, so that it can help doctors to diagnosis efficiently between benign and malignance tumors.

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References

  1. Jung, I., Thapa, D., Wang, G.-N.: Automatic segmentation and Diagnosis of breast lesions using morphology method based on ultrasound. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3612, pp. 1079–1088. Springer, Heidelberg (2005)

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Author information

Authors and Affiliations

  1. Department of Industrial and Information Engineering, Ajou University, South Korea

    In-Sung Jung, Devinder Thapa & Gi-Nam Wang

Authors
  1. In-Sung Jung
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  2. Devinder Thapa
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  3. Gi-Nam Wang
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Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

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© 2005 Springer-Verlag Berlin Heidelberg

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Jung, IS., Thapa, D., Wang, GN. (2005). Neural Network Based Algorithms for Diagnosis and Classification of Breast Cancer Tumor. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_15

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  • DOI: https://doi.org/10.1007/11596448_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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