Preprocessing of magnetic resonance images with multiple Sclerosis lesions

According to the World Health Organization, it is estimated that multiple sclerosis (MS) affects around 2.5 million people worldwide and more than 5000 in Portugal. Multiple sclerosis is an inflammatory, demyelinating, idiopathic, and often disabling central nervous system disease that affects the white matter diagnosed in young adults and predominantly affects womens. Multiple sclerosis is the most common neurological disorder with unexplained causes and major repercussions in the lives of patients, causing the active search for answers by the researchers. Although the disease cannot be cured or prevented at this time, the available treatments only reduce its severity and delay its progression. In recent years, there has been a major development of image processing and analysis techniques in order to facilitate early diagnosis and suitable treatment. In general, images acquired by imaging devices and specialized techniques require transformations and enhancements to make them more suitable in order to extract as much information as desired with greater efficiency. Several authors, have described techniques of image preprocessing and segmentation of MS lesions, making evident the advantages of such computational tools. In this work, different preprocessing algorithms were applied in order to perform the brain extraction from resonance magnetic (RM) images for their easier further analysis.