Brain tumor detection & segmentation using deep learning

Abstract

The goal of this work is to identify brain tumors and improve care for those who are suffering. Tumors are the term used to denote abnormal cell growth in the brain, while cancer is the term used to describe malignant tumors. Brain cancer regions are typically discovered via Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scans. For the detection of brain tumors, further methods include molecular testing, lumbar puncture, cerebral angiogram, and positron emission tomography. Images from an MRI scan are used in this study to analyze the disease stage. The goals of this research are to segment the tumor region and to identify the abnormal image. The segmented mask can be used to evaluate the tumor's density, which will aid in treatment. ResNet algorithm is used to analyze MRI pictures and find anomalies.