title: 3D dendrite reconstruction and spine identification.
abstract: In neuron-biology, 3D neuron dendrite reconstruction followed by spine identification is indispensable for the study of neuronal functions and biophysical properties. In this paper, we propose an automatic dendrite reconstruction method to with a surface representation of the neuron on the basis of a novel level set approach. Our novel level set approach can effectively tackle the problem of segmentation under blurring and intensity in-homogeneity. Then spines are detected based on dendrite medial axis and a label-based thinning strategy is proposed to accurately extract the dendrite skeleton for spine identification. Experimental results reveal that our method works well.
authors.affiliation: Department of EEIS, University of Science and Technology of China, Hefei, PR China. zhwg@mail.ustc.edu.cn
authors.forename: Wengang
authors.initials: W
authors.lastname: Zhou
authors.forename: Houqiang
authors.initials: H
authors.lastname: Li
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Zhou
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003712:Dendrites / Q000648:ultrastructure*; D049229:Dendritic Spines / Q000648:ultrastructure; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018613:Microscopy, Confocal / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity