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Clustered fuzzy-neural machine for classification of cancerous cells

Lookup NU author(s): Ephraim Nwoye, Professor Satnam Dlay, Dr Wai Lok Woo, Khaled Marghani

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Abstract

Computer assisted diagnosis of colorectal cancer has received attention in recent years. The development of an automated algorithmic approach, based on quantitative measurements, would be a valuable tool to the pathologist for fast verification of these colon cancer abnormalities for effective treatment. In this paper a method which automatically locates differences in colon cell images and classy the colon cells into normal and malignant cells is presented. This system is implemented by fuzzifying image feature descriptor fractals and incorporating clustering paradigm with neural network to classify images. The proposed system was evaluated using 116 cancers and 88 normal colon cells images and shown to be more efficient, simple to implement and yields better accuracy than conventional methods. (17 References).


Publication metadata

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

Publication type: Article

Publication status: Published

Journal: WSEAS Transactions on Systems

Year: 2003

Volume: 2

Issue: 3

Pages: 655-659

Print publication date: 01/01/2003

ISSN (print): 1109-2777

Publisher: World Scientific and Engineering Academy and Society


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