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Brain Tumor Classification using RST Features
Medical image processing is the most challenging and emerging field nowadays. Processing of MRI images is one of the part of this field. This work presents a performance of the rough set based approaches to solve various problems in medical imaging such as medical image segmentation, object extraction and image classification. The machine learning algorithms provide optimal solution for the classification task. In this code the machine learning tool is used for the classification task and optimization algorithms are used for the selection of Rough Set Theory (RST) features. Rough set frameworks hybridized with other computational intelligence technologies that include neural networks, particle swarm optimization, support vector machines and Genetic Algorithm are also presented. The optimal outcomes of medical image classification is achieved by the machine learning approaches.