BRAIN TUMOR DETECTION FROM MRI IMAGES USING CNN

Abstract

Brain tumor is the main threat among the people. But currently, it become more advancedbecause of the many Machine Learning techniques. Magnetic Resonance Imaging is the greatesttechnique among all the image processing techniques which scans the human body and gives aclear resolution of the tumors in an improved quality image. The fundamentals of MRI are todevelop images based on magnetic field and radio waves of the anatomy of the body. The majorarea of segmentation of images is medical image processing. Better results are provided by MRIimages than CT scan, Xrays etc. Nowadays the automatic tumor detection in large spatial andstructural variability. Recently Convolutional Neural Network plays an important role in medicalfield and computer vision. One of its application is the identification of brain tumor. Here, thepre-processingtechniqueisusedtoconvertnormalimagestograyscalevaluesbecauseitcontains equal intensity butin MRI, RGB contentis included. Then filtering is used to remove the unwanted noises using median and high pass filter for better quality of images. The deeper architecture design in CNN is performed using small kernels. Finally, the effect of using this network for segmentation of tumor from MRI images is evaluated with better results.