中文摘要：

利用荧光标记显微成像研究树突棘的形态结构是神经学的重要研究手段之一,现阶段在低信噪比图像中对树突棘检测并进行形态学分析主要依赖人工参与,使得分析缺乏客观参照系且极其耗费人力.提出了一种基于断点匹配搜索和分段采样曲线拟合的算法,能够自动检测神经树突的边缘,实现树突与突棘的分离,并计算出繁杂图像的树突与突棘的大小、个数、密度等参量.分析结果表明,此方法为树突棘图像的分析提供了高效、准确的分析工具.

英文摘要：

Fluorescence microscopy imaging is one of the important methods for the study of the dendritic spine structures. Most of the current morphologic analyses in low SNR images involve a significant component of manual labor and is susceptible to operator bias. An algorithm based on endpoint match- searching and segmentation-sampling curve fitting was presented to automatically detect the edge of the dendrite, separate dendritic spines and calculate their size, number and density in complex images. Analysis of the results shows that it provides an efficient, accurate tool for dendritic spine analysis.