Stroke Prediction using MRI Images

Early prediction of stroke plays an important role as it can reduce brain damage and also reduce the consequences caused by the stroke. Stroke is the second leading cause of death all over the world and one of the fatal diseases for people above the age 60 years. So, after considering all these risks we wanted to develop an automated system that could be helpful to predict the stroke in the early stages. Medical imaging is a well-developing technology in recent times and by considering the accuracy that the proposed system should provide we used MRI images as the dataset. In this study, we divided the whole process into six distinctive stages which included three major processes which are Data Collection, Pre-processing of the data, Performance Analysis Method of Classification. And In pre-processing, Gabor filters were used to improve the quality of the MRI images. Adaptive histogram equalization is the(AHE) is the technique used for enhancement.