Three-dimensional motor neuron morphology estimation in the Drosophila ventral nerve cord.
Three-dimensional motor neuron morphology estimation in the Drosophila ventral nerve cord.
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果蝇腹神经索的三维运动神经元形态估计。
DOI：
10.1109/tbme.2011.2181166
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Chiba,Akira
中科院分区：
文献类型：
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作者：
Tsechpenakis,Gavriil;Mukherjee,Prateep;Kim,MichaelD;Chiba,Akira
类型特异性树突树枝化模式决定突触连接，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刻板性和相对简单性来模拟单个运动神经元（MN）的不同神经元形态，并了解运动回路中突触连接的基本原理。我们的计算方法的目的是重建的神经元形态，即强大的分割的神经元体积从他们的周围环境，同时分区到他们的车厢，即索马，轴突和树突。我们使用共同分割的思想，其中每个图像沿着z轴（深度）使用来自“相邻”深度的信息进行分割。我们使用3-D Haar类特征来建模外观。由于索马和轴突是由其独特的形状，我们定义了一个隐式的形状表示的2-D分割集驱动cosegmentation和实现所需的分区。我们验证我们的方法使用图像堆栈描绘单个神经元标记的绿色荧光蛋白（GFP）和连续成像的激光扫描共聚焦显微镜。
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 neuronal morphologies of individual motor neurons (MNs) and understand underlying principles of synaptic connectivity in a motor circuit. Our computational approach aims at the reconstruction of the neuron morphology, namely the robust segmentation of the neuron volumes from their surroundings with the simultaneous partitioning into their compartments, namely the soma, axon, and dendrites. We use the idea of cosegmentation, where every image along the z -axis (depth) is segmented using information from “neighboring” depths. We use 3-D Haar-like features to model appearance. Because soma and axon are determined by their distinctive shapes, we define an implicit shape representation of the 2-D segmentation sets to drive cosegmentation and achieve the desired partitioning. We validate our method using image stacks depicting single neurons labeled with green fluorescent protein (GFP) and serially imaged with laser scanning confocal microscopy.