中国科学技术大学学报 ›› 2014, Vol. 44 ›› Issue (2): 160-164.DOI: 10.3969/j.issn.0253-2778.2014.02.012

• 原创论文 • 上一篇    下一篇

三维显微图像中神经元树突棘自动检测与分析

汪 迁   

  1. 南京大学电子科学与工程学院,江苏南京 210023
  • 收稿日期:2013-06-16 修回日期:2014-02-19 出版日期:2014-02-28 发布日期:2014-02-28
  • 通讯作者: 李杨
  • 作者简介:汪迁,男,1990年生,硕士生. 研究方向:图像处理. E-mail: winnieryl@gmail.com
  • 基金资助:
    国家自然科学基金(61300157,61201425,61271231),江苏省自然科学基金(BK2011337)资助.

Automatic dendritic spine detection and analysis in 3D microscope images

WANG Qian   

  1. School of Electronic Science and Engineering, Nanjing University, Nanjing 210023, China
  • Received:2013-06-16 Revised:2014-02-19 Online:2014-02-28 Published:2014-02-28

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.

关键词: 神经树突, 突棘, 分段采样, 匹配搜索

Abstract: 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.

Key words: dendrite, spine, segmentation-sampling, match-searching