Central Nervous System Tumour Classification Using Residual Neural Network

Abstract

A brain tumor occurs when an abnormal growth of cells form within the brain. There are two main types of tumors: cancerous (malignant) tumors and benign tumors. All types of brain tumors may produce symptoms that vary depending on the part of the brain involved. These symptoms may include headaches, seizures, problems with vision, vomiting, and mental changes. Other symptoms may include difficulty walking, speaking, or sensations. As the disease progresses, unconsciousness may occur. One of the problems that brain tumor diagnosis faces is the similarities of its initial symptoms with that of commonly occurring diseases, making it prone to misdiagnosis. The brain and spinal column make up the central nervous system (CNS), where all vital functions, including thought, speech, and body movements are controlled. This means that when a tumor grows in the CNS, it can affect a person's thought process or the way they talk or move. The main purpose of this project is to build a CNN model that would classify if the subject has a tumor or not based on MRI scans. This would help ensure that proper diagnosis takes place and can help doctors recommend the most effective treatment.