Identifying Demyelinating and Ischemia brain diseases through magnetic resonance images processing

Brain Magnetic Resonance Images are a very useful tool for the diagnosis of brain diseases and analyse brain changes. The appropriate processing (neuroimaging) can help to identify, measure and classify different lesions or abnormalities. The principal aim of this project is to develop an algorithm that can identify and differentiate ischemic disease than the demyelinating disease in the brain through the processing of magnetic resonance images. The damage and deterioration of the myelin layer of nerve fibers (brain demyelination) is the cause of pathologies like multiple sclerosis. Ischemic stroke is produced by the interruption of the blood supply to the brain. The dataset used was composed of images T1, T2 and FLAIR modalities of 90 patients from the hospital. For the segmentation of the features, the identification and the classification of the lesions have used the methods of Discrete Wavelet Transform (DWT), principal component analysis (PCA) and support vector machine (SVM). The results present 60 to 80% of accuracy to identify and differentiate the diseases.