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Tumor Location and size Identification in Brain Tissues Using Fuzzy C-Clustering and Artificial Bee Colony Algorithm
Mr Snehalkumar A. Patel,  Mr Utkarsh V. Shah
Clustering approach is widely used in biomedical applications particularly for brain tumor detection in abnormal magnetic resonance (MRI) images. Fuzzy clustering using fuzzy C-means (FCM) algorithm proved to be superior over the other clustering approaches in terms of segmentation efficiency. MRI imaging forms one of the core methods to identify Brain Tumors, and access the existence, size and thickness of the tumor. MRI Images are prone to high noise, as the whole principle works on strong electric fields. We try to remove the noise using Artificial Bee Colony Algorithm and then try to abstract the tumor part using Fuzzy C-Means Clustering.
Keywords- MR brain tumor, Fuzzy C-Means Clustering, Artificial Bee Colony
Unique Identification Number - IJEDR1403052Page Number(s) - 3231-3234Pubished in - Volume 2 | Issue 3 | Sept 2014DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Mr Snehalkumar A. Patel,  Mr Utkarsh V. Shah,   "Tumor Location and size Identification in Brain Tissues Using Fuzzy C-Clustering and Artificial Bee Colony Algorithm"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.2, Issue 3, pp.3231-3234, Sept 2014, Available at :http://www.ijedr.org/papers/IJEDR1403052.pdf