Graded image segmentation of brain tissue in the presence of inhomogeneous radio frequency fields

Image segmentation is used increasingly to interpret MR spectroscopic data of the brain, using image contrast to identify gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF). T(1)- or T(2)-weighted images are typically used, but poor shimming, susceptibility effects, and small variations in B(1) and receptivity cause difficulties in tissue identification. Quantitative imaging of T(1) can reduce many of these difficulties but is still subject to complications when B(1) has large variations like those observed with the surface coils often used for spectroscopy. In this study, B(1) imaging was implemented to support quantitative imaging of T(1) with either a surface coil or a volume coil. The T(1) observed by this method is a continuous function across mixtures of WM/GM and GM/CSF, and this function was measured and used to convert the images of T(1) to maps of percent GM, WM, and CSF.