title: Thalamus segmentation from diffusion tensor magnetic resonance imaging.
abstract: In this paper, we propose a semi-automatic thalamus and thalamus nuclei segmentation algorithm from diffusion tensor magnetic resonance imaging (DT-MRI) based on the mean-shift algorithm. Comparing with existing thalamus segmentation algorithms which are mainly based on K-means algorithm, our mean-shift based algorithm is more flexible and adaptive. It does not assume a Gaussian distribution or a fixed number of clusters. Furthermore, the single parameter in the mean-shift based algorithm supports hierarchical clustering naturally.
authors.affiliation: Dept. of Comput. Sci., Missouri Univ., Columbia, MO 65211, USA.
authors.forename: Ye
authors.initials: Y
authors.lastname: Duan
authors.forename: Greg
authors.initials: G
authors.lastname: Heckenberg
authors.forename: Yongjian
authors.initials: Y
authors.lastname: Xi
authors.forename: Dayang
authors.initials: D
authors.lastname: Hao
mesh_terms: D001331:Automation; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008959:Models, Neurological; D013787:Thalamic Nuclei / Q000033:anatomy & histology / Q000502:physiology; D013788:Thalamus / Q000033:anatomy & histology* / Q000502:physiology*