Rayburst sampling, an algorithm for automated three-dimensional shape analysis from laser scanning microscopy images
Rayburst sampling, an algorithm for automated three-dimensional shape analysis from laser scanning microscopy images
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DOI：
10.1038/nprot.2006.313
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发表时间：
2006-01-01
期刊：
影响因子：
14.8
通讯作者：
Wearne, Susan L.
中科院分区：
文献类型：
--
作者：
Rodriguez, Alfredo;Ehlenberger, Douglas B.;Wearne, Susan L.
从激光扫描显微镜（LSM）图像中精确量化复杂的三维（3D）结构对于理解生物学中的正常功能和病理过程越来越重要。该协议描述了一种通用的形状分析算法，Rayburst采样，从LSM图像生成自动3D测量。Rayburst定义并有效地投射从内部点到实体表面的多方向射线核心，允许精确量化各向异性和不规则形状的3D结构。由于在数字图像中的有限体素表示的量化误差被最小化的体素之间连续插值强度值。Rayburst算法为解决特定形状分析问题的更高级别算法的开发提供了一个原语。提供的应用程序的3D神经元形态测量的例子：（i）估计管状神经元树突状分支结构的直径，及（ii）树突棘和空间复杂的组织病理学结构的体积和表面积的测量。
Precise quantification of complex three-dimensional (3D) structures from laser scanning microscopy (LSM) images is increasingly necessary in understanding normal function and pathologic processes in biology. This protocol describes a versatile shape analysis algorithm, Rayburst sampling, that generates automated 3D measurements from LSM images. Rayburst defines and efficiently casts a multidirectional core of rays from an interior point to the surface of a solid, allowing precise quantification of anisotropic and irregularly shaped 3D structures. Quantization error owing to the finite voxel representation in digital images is minimized by interpolating intensity values continuously between voxels. The Rayburst algorithm provides a primitive for the development of higher level algorithms that solve specific shape analysis problems. Examples are provided of applications to 3D neuronal morphometry: (i) estimation of diameters in tubular neuronal dendritic branching structures, and (ii) measurement of volumes and surface areas for dendritic spines and spatially complex histopathologic structures.