Abstract—This paper presents a review of the current literature on rough set and near set-based approaches to solving various problems in medical imaging such as medical image segmentation, object extraction and image classification. Rough set frameworks hybridized with other computational

Abstract—This paper presents a review of the current literature on rough set and near set-based approaches to solving various problems in medical imaging such as medical image segmentation, object extraction and image classification. Rough set frameworks hybridized with other computational

Proceedings of the Conference

and Charles Stone (BFOS), represents a milestone in the evolution of Artificial Intelligence, Machine Learning, non-parametric statistics, and data mining. The work is important for the comprehensiveness of its study of decision trees, the technical innovations it introduces, its sophisticated

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