Brain Tumour Segmentation Using Clustering Algorithms
Abstract: The image segmentation is performed to detect, extract and characterize the anatomical structure. Here, we apply two widely used algorithm for tumour detection (i) K-means clustering (ii) Fuzzy C Means clustering The segmentation algorithms are compared to estimate the efficiency by evaluating the execution time and accuracy of the algorithm. The result shows that the execution time is less in K-Means compared to Fuzzy C Means clustering technique, because the number of iterations of K-Means is less than Fuzzy C Means clustering. Further, the tumour area is calculated for accurate result.
Keywords: Image segmentation, K-Means clustering, Fuzzy C means clustering techniques, Segmentation algorithms
How to Cite?: Varsha A. Kshirsagar, J. R. Panchal, "Brain Tumour Segmentation Using Clustering Algorithms", Volume 4 Issue 9, September 2015, International Journal of Science and Research (IJSR), Pages: 356-359, https://www.ijsr.net/getabstract.php?paperid=SUB157991, DOI: https://dx.doi.org/10.21275/SUB157991