Segmenting gray matter structures within the thalamus is complicated by poor inherent T1/T2 contrast. Most existing approaches focus on clustering diffusion data including fiber orientation and short & long distance diffusion directions. We propose a hybrid approach incorporating diffusion data with a recently-developed high T1 contrast imaging sequence known as FGATIR. The proposed algorithm clusters on spatial position, fiber orientation distribution coefficients and anatomical contrast to provide robust, yet fast and fully-automatic segmentation of the thalamic nuclei showing strong agreement to manual segmentation performed by a neuroradiologist. Reliable thalamic nuclei segmentation could facilitate targeted therapies like deep brain stimulation.