• C.Hari Prasad
• S.Shafiulla Basha
• P.Sandhya
• V.Sisira
• K.Harish Narayana

Brain tumor is one of disease type that attacks the brain in the form of clots. There was a way to see brain tumor in detail required by an MRI image. There is difficulty in distinguishing brain tumor tissue from normal tissue because of the similar color. Brain tumor must be analyzed accurately. The solution for analyze brain tumor is doing segmentation. Brain tumor segmentation is done to separate brain tumor tissue from other tissues such as fat, edema, normal brain tissue and cerebrospinal fluid to overcome this difficulty. In this study, we performed pre-processing using the bilateral filter for removal of the noises that are present in an MR image. This was followed by the Convolution Neural Network (CNN) segmentation technique for reliable detection of the tumor region. The resultant outcomes will be examined through various performance examined metrics that include accuracy, precision, and specificity. It is desired that the proposed work would exhibit a more exceptional performance over its counterparts.

Brain Tumor, MRI image, Bilateral Filtering, Convolutional Neural Network.

"Brain Tumor Segmentation using RESNET 50 algorithm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.g259-g261, April-2022, Available :http://www.jetir.org/papers/JETIR2204638.pdf

"Brain Tumor Segmentation using RESNET 50 algorithm ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppg259-g261, April-2022, Available at : http://www.jetir.org/papers/JETIR2204638.pdf