Analysis of Brain Tumor Detection Using Machine Learning

In the field of medical sciences, early detection can lead to increased rate of survival. Proper diagnosis is helpful for the radiologists in evaluating the false positive and true negative cases. Many traditional methods have been applied for detecting the tumor. Nowadays, automated methods are being applied using artificial intelligence with machine learning techniques to obtain better and precise results. Automated detections of tumor in MRI images play a very pivotal role for planning post-treatments for the patients who are suffering from it. These automated defect detection techniques are applied to solve problem of impractical results which is generated on analyzing the bigger amount of medical images data and saves the radiologist’s time because the detection of tumor is very complex task due to variations and complexity in brain tumors. In this paper, the tumor is detected in brain using MRI images by applying machine learning algorithms for attaining better classification rates.