Automated Brain Tumor Identification in MRI Scans Using State-of-the-Art Deep Learning Models

A lump or development of aberrant cells in your brain that grows unhindered is called a brain tumour. Cancer or tumours may begin in the brain or spread there from other parts of the body. Early brain cancer detection is an extremely difficult task for radiologists. Brain tumours grow quickly; they often double in size in 25 days. Patients who receive inadequate treatment typically have a survival rate of no more than six months. It can quickly result in death. Because of this, an automated approach is necessary to detect brain tumours at an early stage. This idea suggests an automated technique for quickly distinguishing between a cancer and a healthy brain using the brain's magnetic resonance imaging (MRI). Convolutional Neural Networks (CNN), two deep learning principles, are used in this research. Two models-one with two convolutional layers and the other with two fully linked layers-are displayed in this research. And the second model, which has three fully, linked layers and four convolutional layers. When testing these models, satisfactory accuracy was attained; hence, radiologists can use this method in real life to promptly identify cancers and take action that could potentially save lives.