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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