Improvement of Pseudo Multispectral Classification of Brain MR Images

Abstract — Classification of brain tissues is becoming an increasingly useful tool for investigating the aging brain or disease-induced brain alterations. Numerous strategies have been proposed to classify brain tissues into white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). How-ever, many of them fail when classifying specific regions with low contrast between tissues (e.g. cerebellum gray and white matter). Erroneous classification may lead to volume over- or under-estimation, thus leading to equivocal interpretations. In this work, instead of using gray scale images (T1-MPRAGE) to classify brain tissues, we use an improved pseudo multispectral classification (PMC) technique using CIE XYZ spaces and iterative K-mean clustering in order to enhance classification of the brain GM, WM and CSF. The accuracy of the proposed approach is assessed using atlas brain templates and compare