Identifying multiple sclerosis lesions in MR images using image processing techniques

Multiple sclerosis (MS) is a disease of the central nervous system (CNS), it is inflammation or decay in a myelin's substance (Demyelination). The causes of the disease is unknown yet, but it is believed to be caused by a combination of many genetic and environmental factors including: geographical distribution (i e less spread closer to the equator), and hereditary reasons. Currently, the diagnosis is depending on the clinical diagnosis of the symptoms of the disease, but the evolution in medical imaging (eg. MRI) can help in detecting the presence of lesions in the white or gray matter of the brain's tissues. In this research, many digital image processor techniques have been adopted and used to detect the lesions sites. An adaptive method is introduced to skinning the brain tissue from the skull's bones. Many edges detection methods have been suggested to segment the MRIs brain tissues (i. e first and second order differentiation methods). The second order Marr-Hildreth method is adopted because it produces thin edge and connected boundaries.