A Parallel System for the Classification of Cancerous and Normal Colonic Mucosa Tissue Images

J. Filippas, S.A. Amin, R.N.G. Naguib, and M.K. Bennett (UK)


Medical Images, Image Classification, PVM, TextureAnalysis.


Analysis of tissue using image processing techniques is useful for dealing with a number of problems in cancer research. Ideally in the future it will be possible to construct a fully automated computer system, one that can perform image classification without requiring human intervention. The aim of this research is to develop a system for performing classification of cancerous, dysplastic or normal colonic mucosa tissue images, by means of identifying the image processing techniques required, and experimenting with various classification techniques. A number of co-occurrence matrix feature extraction algorithms have been selected and are presented in this paper. Since analysis of tissue images is a complex task requiring vast processing power, parallel computing techniques have been employed. The classification system was implemented by means of a C++ library for distributed system programming using PVM (Parallel Virtual Machine) on a cluster of workstations. The performance and accuracy of the system are discussed in this paper.

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