Thalamus segmentation from diffusion tensor magnetic resonance imaging.
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.
Duan
Ye
Y
Dept. of Comput. Sci., Missouri Univ., Columbia, MO 65211, USA.
Heckenberg
Greg
G
Xi
Yongjian
Y
Hao
Dayang
D
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*