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An Effective Image Feature Classiffication using an improved SOM
In this paper, a novel Self Organizing Map, termed improved SOM (iSOM), is proposed with the aim of effectively classifying Mammographic images based on their texture feature representation.
Self Organization Map based Texture Feature Extraction for Efficient Medical Image Categorization
In this approach, we apply three different partitioning approaches as a region of interested (ROI) selection methods for extracting different accurate textural features from medical image as a primary step of our extraction method.
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