Tsechpenakis Gavriil, Gamage Ruwan Egoda, Kim Michael D, Chiba Akira
Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:7755-8. doi: 10.1109/IEMBS.2011.6091911.
Type-specific dendritic arborization patterns dictate synaptic connectivity and are fundamental determinants of neuronal function. We exploit the morphological stereotypy and relative simplicity of the Drosophila nervous system to model the diverse dendritic morphologies of individual motor neurons (MNs) to understand underlying principles of synaptic connectivity in a motor circuit. The genetic tractability of Drosophila allows us to label single MNs with green fluorescent protein (GFP) and serially reconstruct identifiable MNs in 3D with confocal microscopy. Our computational approach aims at the robust segmentation of the MN volumes and the simultaneous partitioning into their compartments, namely the soma, axon and dendrites. We use the idea of co-segmentation, where every image along the z-axis (depth) is clustered using information from 'neighboring' depths. As appearance we use a 3D extension of Haar features and for the shape we define an implicit representation of the segmentation domain.
特定类型的树突分支模式决定了突触连接，并且是神经元功能的基本决定因素。我们利用果蝇神经系统的形态学刻板性和相对简单性，对单个运动神经元（MN）的多种树突形态进行建模，以了解运动回路中突触连接的潜在原理。果蝇的遗传易处理性使我们能够用绿色荧光蛋白（GFP）标记单个MN，并通过共聚焦显微镜以三维方式连续重建可识别的MN。我们的计算方法旨在对MN体积进行稳健分割，并同时将其划分为不同的部分，即胞体、轴突和树突。我们采用共分割的理念，其中沿z轴（深度）的每个图像都利用来自“相邻”深度的信息进行聚类。在外观方面，我们使用哈尔特征的三维扩展，对于形状，我们定义了分割域的隐式表示。
