A distributed system for the classification of cancerous and normal colonic mucosa tissue images

Analysis of tissue using image processing techniques is useful for dealing with a number of problems in cancer research. One such problem is the identification of normal, dysplastic and cancerous colonic mucosa. This research aims to identify the main image processing techniques necessary for this particular task, and to develop an automatic image classification system. Several texture analysis image-processing algorithms have been employed in this paper. Those can be separated into three categories, histogram features, grey-level difference statistics and co-occurrence matrix feature extraction algorithms. The classification system is implemented on a distributed system using PVM (Parallel Virtual Machine). PVM is a library for distributed application programming.