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Tumor is an uncontrolled development of tissue in any part of the body. The tumor is of various sorts and they have different characteristics and different treatment. This paper is to execute of Simple Algorithm for discovery of range of tumor in brain MR Images. Typically the anatomy of the Brain can be seen by the MRI scan or CT scan. MRI scanned picture is utilized for the whole procedure. The MRI output is more agreeable than any different scans for finding. It won't influence the human body, since it doesn't practice any radiation. It is focused on the magnetic field and radio waves. There are disparate sorts of calculation were created for brain tumor recognition. But they may have some drawback in detection and extraction. After the segmentation, which is done through k-means clustering and fuzzy c-means algorithms the brain tumor is distinguished and recognized. The patient's stage is dictated by this handle, regardless of whether it can be cured with solution or not.
Keywords:
Magnetic resonance image, Image segmentation, K-Means clustering, Fuzzy c-means
Cite Article:
"BRAIN TUMOR DETECTION USING K-MEANS CLUSTERING AND FUZZY C-MEANS ALGORITHMS", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 3, page no.60 - 63, March-2017, Available :http://www.ijrti.org/papers/IJRTI1703012.pdf
Downloads:
000204835
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator