A Study on Rough Set Theory for Medical Image Segmentation
نویسنده
چکیده
Rough set is approximate representation of a crisp set. Rough set theory provides an approach to approximation of sets that leads to useful forms of granular computing. Several applications have revealed the need to extend the traditional rough set approach. A special place among various extensions is taken by the approach that replaces the relation based on equivalence with a tolerance relation. Rough sets offer an effective approach of managing uncertainties and can be employed for tasks such as feature identification, dimensionality reduction, pattern classification and image segmentation. In this paper, the main aim is to survey the Rough set Theory for medical image
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