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Brain Tumor Detection

EasyChair Preprint no. 3266

6 pagesDate: April 26, 2020


A tumor is a lump that grows abnormally without any control. It can be dangerous in most cases. At an early stage, a brain tumor can be a strenuous task even for doctors to figure out. Using MRI Images is not always reliable, as they contain noise and other disturbances, so hence it becomes difficult for doctors to identify tumor and their causes. So, this is where Image Processing comes, few of  it’s techniques are used to recognize the image of interest in order to visualize the images easily. We propose a system which detects tumor from brain MRI images. First, we do processing of the image by converting the given image into a grey scale image and some filters are applied to filter noise and other disturbances from the image and find out contours of the image,then we construct the CNN layers and perform classification using CNN(Convolution neural network).This suggested work accomplishes brain tumor prediction and detection using keras and tensorflow, in which anaconda framework is used.

Keyphrases: Accuracy, Anaconda Framework, Brain Tumor, Brain tumor detection system, Keras, prediction, TensorFlow

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Kodali Keerthi and Sai Deepika Bhuvanagiri Yasaswini and Atmuri Rajkumar and Alacarthi Jitendra},
  title = {Brain Tumor Detection},
  howpublished = {EasyChair Preprint no. 3266},

  year = {EasyChair, 2020}}
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