Classification of cancerous cells images using clustered fuzzy-neural machine techniques (2004)

Author(s): Nwoye E, Dlay SS, Woo WL

    Abstract: Computer assisted diagnosis of cancer has received attention in recent years. The development of automated algorithms would be a valuable tool to the Pathologist for fast verification of these cancer abnormalities. In this paper a novel method which will automatically locate differences in cancer cells images and classy cells into normal and malignant is implemented by fuzzifying image feature descriptor values and incorporating clustering paradigm into neural network to classify images. The proposed system was evaluated using 116 cancers and 88 normal colon cells images. It is more efficient, simple to implement and yields better accuracy than conventional methods. (7 References).

    Notes: Dlay SS Newcastle upon Tyne, UK. Communication Systems, Networks and Digital Signal Processing. CSNDSP 2004. Fourth International Symposium. Newcastle upon Tyne, UK. 20-22 July 2004.

      • Date: 20-22 July 2004
      • Conference Name: Communication Systems, Networks and Digital Signal Processing (CSNDSP)
      • Pages: 491-494
      • Publication type: Conference Proceedings (inc. abstract)
      • Bibliographic status: Published

        Professor Satnam Dlay
        Professor of Signal Processing Analysis

        Dr Wai Lok Woo
        Director of Singapore Operations