Performance Analysis of Deep Learning Techniques on Automatic Brain Tumour Grading

In recent decades, there has been a lot of research in the subject of image processing. The detection of brain tumours in biomedical engineering, plays a critical role and has been a time-consuming effort in detecting the disease. The death rate increased as a result of the formation of a brain tumour, which leads to cancer. It is difficult to detect brain tumour at an early stage. Early detection of a brain tumour may save people's lives and keep them out of danger. In order to detect the brain tumour, several theories and procedures were researched and adopted. In this work, variety of information, collected from various sources, including journals, scholarly evidence. Different approaches and algorithms for diagnosing brain tumour are studied and their performance are analysed. The analysis shows that implementing a deep convolution neural network for diagnosing brain tumours gives improved results.