Brain tumor segmentation using convolutional neural network

Nowadays health is an essential factor in human life, among all the health complexities brain tumors are very critical to deal with. Though there are some existing techniques to classify the brain related deficiencies, there is no proper method to segment the process. MRI (Magnetic Resonance Imaging) and ultrasound techniques are vastly used in order to classify the brain condition all over the world lately. But there exist some limitations among those processes to keenly classify the brain tumor analysis, this segmentation using CNN is now very trusted as it has more accuracy compared to all the existing methods. This is introduced which can be applied using image detection and convolutional neural networks. Algorithm which is within popular and well motivating classification methods. The CNN produces an accuracy of 99.3% which is higher than any other existing methods and is low in complexity. Small kernels are used to perform this design.