Rodriguez Alfredo, Ehlenberger Douglas B, Hof Patrick R, Wearne Susan L
Fishberg Department of Neuroscience, Mount Sinai School of Medicine, New York, New York 10029, USA.
Nat Protoc. 2006;1(4):2152-61. doi: 10.1038/nprot.2006.313.
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.
在理解生物学中的正常功能和病理过程时，从激光扫描显微镜（LSM）图像中精确量化复杂的三维（3D）结构变得越来越必要。本方案描述了一种通用的形状分析算法——射线爆发采样，它可从LSM图像生成自动的3D测量结果。射线爆发定义并有效地从内部点向固体表面投射多方向的射线核心，从而能够精确量化各向异性和形状不规则的3D结构。通过在体素之间连续插值强度值，可将数字图像中由于有限体素表示而产生的量化误差降至最低。射线爆发算法为解决特定形状分析问题的高级算法开发提供了一个原语。文中给出了其在3D神经元形态测量中的应用示例：（i）估计管状神经元树突分支结构中的直径，以及（ii）测量树突棘和空间复杂的组织病理学结构的体积和表面积。
