An Efficient Image Processing Technique for Brain Tumor Detection from MRI Images

Brain tumor, a type of cancer, is caused by a genetic mutation of abnormal neuronal cells. However, it cannot be easily diagnosed and depends on the patient’s symptoms which range from hemialgia, seizure, irregular vision, mental shift and many more. The symptoms may vary depending on the region of the tumor. Currently, Magnetic Resonance Imaging (MRI) scan is the foremost means for tumor detection as well as identifying the position and extent of the tumor for surgical procedure. However, the MRIs are needed to be manually checked by a professional to determine the results. We propose a system which is an effective image processing algorithm for detecting and recognizing the tumor from MRI images to obtain the image segmentation of brain bleeding more accurately, making immediate medical treatment possible. In this system, the same problem with different procedures and methods is tested to find the best conjunction through trial and error. Through the combination, the effectiveness and error ratio of the results is engrossed on. This approach is for early detection of brain tumors with high correctness which gives an adequate result by detecting brain tumor properly.