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Biennial International Conference on Information Processing in Medical Imaging

IPMI 1991: Information Processing in Medical Imaging pp 434–443Cite as

Learning of uncertain classification rules in biomedical images: The case of colposcopic images

  • 8. Rule Based Systems And Learning
  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 511))

Abstract

Knowledge acquisition is always a critical step in the development of a knowledge-based computing system. In the particular area of the interpretation of biomedical images, the assignement of meanings to image patterns is based on obscure and intrinsically vague criteria which are difficult to asses and transform into a suitable machine representation. Automatic learning tecniques may be a promising tool in addressing this problem. The paper illustrates a methodological procedure based on fuzzy set theory and using fuzzy logic for the automatic learning of classification rules for biomedical image interpretation systems. It also provides a detailed description of the application of the procedure in the development of a system for the automatic detection of preneoplastic and neoplastic lesions in colposcopic images. Plans to employ the system contemplate its use in educational applications, in diagnostic review for research purposes, and as an online support in clinical practice.

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Author information

Authors and Affiliations

  1. Istituto di Fisica Cosmica e Tecnologie Relative, C.N.R. Milano, Via Ampere 56, 20133, Milano, Italy

    E Binaghi & A Rampini

Authors
  1. E Binaghi
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  2. A Rampini
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Editor information

Alan C. F. Colchester David J. Hawkes

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© 1991 Springer-Verlag Berlin Heidelberg

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Binaghi, E., Rampini, A. (1991). Learning of uncertain classification rules in biomedical images: The case of colposcopic images. In: Colchester, A.C.F., Hawkes, D.J. (eds) Information Processing in Medical Imaging. IPMI 1991. Lecture Notes in Computer Science, vol 511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033771

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  • DOI: https://doi.org/10.1007/BFb0033771

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54246-9

  • Online ISBN: 978-3-540-47521-7

  • eBook Packages: Springer Book Archive

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