Zhou Wengang, Li Houqiang, Zhou Xiaobo
Department of EEIS, University of Science and Technology of China, Hefei, PR China.
Med Image Comput Comput Assist Interv. 2008;11(Pt 2):18-26. doi: 10.1007/978-3-540-85990-1_3.
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.
在神经生物学中,三维神经元树突重建及随后的棘突识别对于研究神经元功能和生物物理特性而言不可或缺。在本文中,我们基于一种新颖的水平集方法,提出了一种用于神经元表面表示的自动树突重建方法。我们新颖的水平集方法能够有效解决模糊和强度不均匀情况下的分割问题。然后基于树突中轴线检测棘突,并提出一种基于标记的细化策略来准确提取用于棘突识别的树突骨架。实验结果表明我们的方法效果良好。