• T. Lakshmi Narayana
• T. Sreenivasulu Reddy

Brain tumor is one the major cause to death among the people in the world. It can effect at any age of the people. Early detection and diagnosis of the brain tumor reduces the mortality. MRI is the majority preferred screening modality of detection of tumor in brain. Manual detection of tumor from brain MRI images causes misidentification and misclassification which leading to increase the false rate and reduces the accuracy of tumor detection. An automatic brain tumor detection technique can reduce the false finding rate and increases the accuracy of tumor detection from MRI images. In this paper, we proposed different techniques of tumor detection and classification from brain MRI images.

Brain Tumor Detection, FCM, K-Means Clustering, Otsu’s thresholding

"Techniques for Detection and Classification of Brain Tumor from MRI Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.159-163, February-2019, Available :http://www.jetir.org/papers/JETIRAB06030.pdf

"Techniques for Detection and Classification of Brain Tumor from MRI Images", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp159-163, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06030.pdf