Abstract

Now a day’s tumor is second leading cause of cancer. Currently Doctors locate the positions and area of a brain tumor by looking at the MRI of the brain manually. This project helps to reduce the inaccuracy and time consumption in detection, and it also provides information about brain. This study presents Convolution neural network architecture for brain tumour detection and classification using magnetic resonance imaging (MRI) as datsets. The performance of the model is to predict whether the given image is tumours or non tumours and classify the tumour image and using use classification to classify brain tumors into three categories: glioma, meningioma, and pituitary tumors and implemented in an Android application.

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