Neural Machine for classification of cancerous cell
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Date
2003-07-01
Authors
Nwoye, E. O.
Dlay, S. S.
Woo, W. L.
Maghani, K. A.
Journal Title
Journal ISSN
Volume Title
Publisher
WSEAS Transactions. on Systems
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 novel method which will automatically locate differences in colon cell Images and classy the colon cell 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 88normal colon cells images and shown to be more efficient, simple to implement and yield better accuracy than conventional methods
Description
Keywords
Fuzzy logic , Neura Network , Clustering Algorithms , Cancerous Cells