@Article{, title={CT Image Segmentation Based on clustering Methods}, author={Asmaa A. Ajwad اسماء جواد and Rand K. Mohammed رند محمد}, journal={Journal of the Faculty of Medicine Baghdad مجلة كلية الطب}, volume={52}, number={2}, pages={234-238}, year={2010}, abstract={Background: image processing of medical images is major method to increase reliability of cancer diagnosis.Methods: The proposed system proceeded into two stages: First, enhancement stage which was performed using of median filter to reduce the noise and artifacts that present in a CT image of a human lung with a cancer, Second: implementation of k-means clustering algorithm.Results: the result image of k-means algorithm compared with the image resulted from implementation of fuzzy c-means (FCM) algorithm. Conclusion: We found that the time required for k-means algorithm implementation is less than that of FCM algorithm.MATLAB package (version 7.3) was used in writing the programming code of our work.Keywords: CT, Image Segmentation, k-mean Clustering, Median Filtering

} }