• Mrs. Nandhini A
• Sathiyaseelan M

An abnormal and uncontrollable development of brain cells is known as a brain tumor. Because of the problems with the brain's anatomy, diagnosing a brain tumor can be difficult. These magnetic resonance images that were gathered as big data can be used to identify brain cancers. We can detect a variety of disorders and investigate the development of the human brain using the rich anatomical information obtained from these MR images. Because of the large image library, brain tumor identification becomes increasingly difficult. Therefore, an algorithmic method is needed to provide a more rapid and accurate clinical diagnosis. In order to precisely diagnose the area of brain tumor, the primary focus of this work is the brain segmentation of MR images using the k-means clustering algorithm. The brain tumor is found following segmentation, which is done using the k-means clustering algorithm.

Brain tumor, detection and segmentation, magnetic resonance imaging (MRI), k-means clustering algorithm

"BRAIN TUMOR SEGMENTATION USING K-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.e320-e324, September-2024, Available :http://www.jetir.org/papers/JETIR2409440.pdf

"BRAIN TUMOR SEGMENTATION USING K-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppe320-e324, September-2024, Available at : http://www.jetir.org/papers/JETIR2409440.pdf