Vol. 5 (06) pp. 1572-1578 DOI: 10.21474/IJAR01/4573

A HYBRID SELF-ORGANIZING MAP WITH FUZZY K-MEANS ALGORITHM FOR BRAINTUMOR IDENTIFICATION AND ANALYSIS USING MAGNETIC RESONANCE BRAIN IMAGES.

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  • Department of Biomedical Engineering, Hebei University of Technology, Tianjin, 300130, China.
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Abstract

Medical image processing is considered the area a great challenge for researchers because of the complexity of this area and its importance to help doctors to diagnose patients effectively. Here we will base on magnetic resonance brain images processing trough the image processing technique is hybrid self-organizing map (SOM) with fuzzy k-means (FKM) algorithm, which gives successfully on tumor and excellent areas within the brain tissue, we propose improved algorithm is accurate and efficient in term of accuracy detection, n Jaccard coif, nDice (DOI), sensitivity, specificity, recall, precision, performing segment. At the same time, the improved algorithm proposed provides the best information and functions, as well as the efficiency and accuracy to handle high input brain MR images.

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How to Cite This Article

Isselmou Abd El Kader, Shuai Zhang and Guizhi Xu. (2017); A HYBRID SELF-ORGANIZING MAP WITH FUZZY K-MEANS ALGORITHM FOR BRAINTUMOR IDENTIFICATION AND ANALYSIS USING MAGNETIC RESONANCE BRAIN IMAGES., Int. J. of Adv. Res., 5 (06), 1572-1578, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/4573

Corresponding Author

Abd El kader Isselmou
Hebei University of Technology
Creative Commons Attribution 4.0 This work is licensed under a Creative Commons Attribution 4.0 International License.