Performance Evaluation of K-Means and Fuzzy C-Means Clustering Algorithms for Identification of Hematoma in Brain CT scan Images

Bhavna Sharma, Prof. K. Venugopalan


Clustering is the assignment of a set of observations into subsets, called clusters so that observations in the same cluster are similar in some sense. This research paper deals with two of the most delegated clustering algorithms namely centroid based K-Means and Fuzzy C-Means for identification of hematoma in brain CT scan. The behaviour of both the algorithms depends upon the brain CT images as well as on the number of clusters. The performance of both the algorithms is investigated during different executions on the input images. The execution time for each algorithm is also analyzed and the results are compared with one another.


Keywords: Fuzzy C-Means Clustering, K-Means Clustering.

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