• Mr.P.E.Elango
• Mr.N.Prabhu
• Mrs.K.A.Poornima
• Dr.S.Subbaiah
• Dr.M.Shanthakumar

Brain tumor disease recognition without human obstruction is a noteworthy test in the field of medicinal picture handling. Division of MRI cerebrum pictures is a method utilized as a first advance towards extricating distinctive highlights from these pictures for breaking down, deciphering and understanding. The goal of MRI mind division is to distinguish the sort of cerebrum variation from the norm. Numerous division systems have been proposed in the writing. These procedures utilize Gaussian conveyance to appraise the picture limit. Gaussian appropriation accepts that the histogram of the picture has symmetric dispersion. Be that as it may, if the histogram is non-symmetric, a more bland dissemination, i.e. a Gamma appropriation, must be utilized. The point of this paper is to improve Li's technique that has been demonstrated useful for picture division, by utilizing Between-Class Variance with Gamma dispersion's. The proposed strategy will be tried on MRI mind pictures. Examinations indicate great outcomes for our improved division recipe. The amazing development in picture preparing for talking about therapeutic imaging is one of the rising field and the necessities for headway's in restorative imaging is dependably developing and testing. Picture division assumes crucial part in picture preparing as it encourages in the extraction of suspicious districts from the MR Images.

Image Segmentation, MRI, Brain Tumor.

"Brain Tumor Detection Using Segmentation Technique for MRI Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.824-827, August-2018, Available :http://www.jetir.org/papers/JETIR1808273.pdf

"Brain Tumor Detection Using Segmentation Technique for MRI Image", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp824-827, August-2018, Available at : http://www.jetir.org/papers/JETIR1808273.pdf