期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2011
卷号：34
期号：1
页码：100-105
出版社：Journal of Theoretical and Applied
摘要：In this paper, we propose a clustering algorithm to deal with the medical image categorization. The algorithm implements an approach, which accepts a set of medical images as categorical input. The categorical inputs are compared with the given pool of images and the result is given in the form of boolean points. The Jaccard co-efficient similarity method does the classification by identifying the neighbors. The higher order co-occurrences with χ-sim Algorithm[2], which has been used for text categorization is implemented for identifying the similarity between images. The proposed approach is tested on images of different sets
