Brain Tumour Detection

A Brain Tumor is a life-threatening disease that disturbs the normal working procedure of the brain and can also change life upside down. To recover from the Brain Tumour Cancer, it is very much necessary that it should be detected and reported at the very early stage. Deep Learning Techniques for Image analysis and Detection play a crucial role in the field of medicine with better accuracy and results. The process of separating the Normal Brain cell or tissues from the abnormal ones after their detection is known as Segmentation. In the earlier phase of research, there was a hypothesis created that states the semi and fully automatic detection and segmentation of brain tumors. But then this proposed theory wasn’t much accurate in the practical phase. In this article, there are many techniques discussed for Brain Tumour Detection according to the past research done in this field. To study brain tumor detection and segmentation MRI Images is very useful in recent years. Due to MRI Images, we can detect the brain tumor. For detection of unusual growth of cells and blocks of tissues in the nervous system can be seen using the help of MRI Images. The basic step of detection of brain tumor cells is to check the symmetric and asymmetric Shape of the brain which will define the abnormality. Then after we need to classify it as Tumored Cell and Non-Tumored Cell.

‍

Hence This project is about the comprehensive analysis of finding the optimal model for detecting brain tumor.