• Pushpa Yadav
• Sonam Yadav

The aim of this paper is to represent an algorithm for automatic detection of tumor in brain from MRI images. Tumor is an abnormal mass of tissue within which some cells grow and multiply uncontrollably. Brain tumor detection using image segmentation is a challenging problem in field of computer vision and image processing because of the diverse image content, non-uniform object texture, image noise and other factors. According to the most research it is observed that due to late or inaccurate detection of tumor the number of people who has brain tumor died. So, the early detection of tumor can be helpful in curing of the disease. It can also be helpful in predicting whether the detected area in MRI image is part of tumor or not. If it shows increasing dimension or growth of the cells then can be predicted as tumor. Accurate detection of size and location plays very vital role in the diagnosis of brain tumor. This paper presents an associated algorithm for a technique that is employed for automatic detection of brain tumor in MRI images.

Brain tumor, Image processing, Support vector machine, Magnetic resonance imaging

"Brain tumor detection based on Support vector machine and FBB algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.220-223, June-2019, Available :http://www.jetir.org/papers/JETIR1906761.pdf

"Brain tumor detection based on Support vector machine and FBB algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp220-223, June-2019, Available at : http://www.jetir.org/papers/JETIR1906761.pdf