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Classifications of Liver Diseases from Medical Digital Images

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Advances in Neural Networks - ISNN 2008 (ISNN 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5264))

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Abstract

Hepatitis B/C virus (HBV/HCV) infections are serious problems of world-wide, which cause over million die each year. Most of HBV/HCV patients need long term therapy. Side effects and virus mutations make difficult to determine the durations and endpoints of treatments. Medical images of livers provide evaluating tools for effectiveness of anti-virus treatments. This paper presents a liver hepatitis progression model. Each class C i in the model consists of three characteristic qualities: gray-scale characteristic interval I G, i , non-homogenous degree N h, i and entropy Entro i . This model aims to describe both digitally and visually a patient’s liver damage. Examples are given to explain how to use the liver hepatitis progress model to classify people with normal livers, healthy HBV carriers, light chronic HBV patients and chronic cirrhosis HBV patients. The results show that our analysis results are in agreement with the clinic diagnoses and provide quantitative and visual interpretations.

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Author information

Authors and Affiliations

  1. Applied Science School/Information Engineering School, University of Science and Technology Beijing, Beijing, 100083, P.R. China

    Lequan Min

  2. Beijing University of Chinese Medicine, Beijing, 100700, P.R. China

    Yongan Ye & Shubiao Gao

Authors
  1. Lequan Min
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  2. Yongan Ye
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  3. Shubiao Gao
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghu University, 100084, Beijing, China

    Fuchun Sun

  2. Institute TAMS (Technical Aspects of Multimodal Systems), department of Informatics, University of Hamburg, Vogt-Koelln-Straße 30, 22527, Hamburg, Germany

    Jianwei Zhang

  3. Intel China Research Center, 8/F, Peking University, Department of Machine Intelligence, 100871, Beijing, China

    Ying Tan

  4. Department of Mathematics, Southeast University, 210096, Nanjing, China

    Jinde Cao

  5. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, 07360, México D.F., México

    Wen Yu

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© 2008 Springer-Verlag Berlin Heidelberg

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Min, L., Ye, Y., Gao, S. (2008). Classifications of Liver Diseases from Medical Digital Images. In: Sun, F., Zhang, J., Tan, Y., Cao, J., Yu, W. (eds) Advances in Neural Networks - ISNN 2008. ISNN 2008. Lecture Notes in Computer Science, vol 5264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87734-9_50

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  • DOI: https://doi.org/10.1007/978-3-540-87734-9_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87733-2

  • Online ISBN: 978-3-540-87734-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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