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Keywords = template-based K-means and modified fuzzy C-means (TKFCM)

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18 pages, 1808 KB  
Article
Automatic Human Brain Tumor Detection in MRI Image Using Template-Based K Means and Improved Fuzzy C Means Clustering Algorithm
by Md Shahariar Alam, Md Mahbubur Rahman, Mohammad Amazad Hossain, Md Khairul Islam, Kazi Mowdud Ahmed, Khandaker Takdir Ahmed, Bikash Chandra Singh and Md Sipon Miah
Big Data Cogn. Comput. 2019, 3(2), 27; https://doi.org/10.3390/bdcc3020027 - 13 May 2019
Cited by 159 | Viewed by 15289
Abstract
In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting human brain tumors [...] Read more.
In recent decades, human brain tumor detection has become one of the most challenging issues in medical science. In this paper, we propose a model that includes the template-based K means and improved fuzzy C means (TKFCM) algorithm for detecting human brain tumors in a magnetic resonance imaging (MRI) image. In this proposed algorithm, firstly, the template-based K-means algorithm is used to initialize segmentation significantly through the perfect selection of a template, based on gray-level intensity of image; secondly, the updated membership is determined by the distances from cluster centroid to cluster data points using the fuzzy C-means (FCM) algorithm while it contacts its best result, and finally, the improved FCM clustering algorithm is used for detecting tumor position by updating membership function that is obtained based on the different features of tumor image including Contrast, Energy, Dissimilarity, Homogeneity, Entropy, and Correlation. Simulation results show that the proposed algorithm achieves better detection of abnormal and normal tissues in the human brain under small detachment of gray-level intensity. In addition, this algorithm detects human brain tumors within a very short time—in seconds compared to minutes with other algorithms. Full article
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