基于骨架树的荧光共焦图像神经树突棘自动分割与检测方法  

Approach for automated segmentation and detection of dendrites and spines from fluorescence confocal image based on skeleton tree

作　　者：张建明[1] 任鑫博[1] 张梵彪[2] 张小丽[1] 

机构地区：[1]江苏大学计算机科学与通信工程学院,江苏镇江212013 [2]南京理工大学计算机科学与技术学院,南京210094

出　　处：《计算机应用研究》2012年第1期340-343,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(60802039);江苏省自然科学基金资助项目(BK2010488);南京理工大学自主科研计划资助项目(2010ZDJH07)

摘　　要：提出一个荧光共焦图像中神经树突棘自动分割与检测方法。该方法采用新的自适应区域生长法对神经树突棘目标进行预分割,基于种子点的路径规划算法,以计算给定点到目标点的最短路径来获取初始主骨架;通过建立最小生成树描述模型对骨架进行修剪,利用种子点间的矢量角度变化及顶点距离值对突棘进行检测提取。实验结果表明,该方法能很好地提取树突骨架,并取得了较好的突棘检测效果。This paper proposed an approach for automated segmentation and detection of dendrites and spines from fluorescence confocal image.It presented a new adaptive region growing algorithm to the segmentation of the dendrite spines for the preprocessing at the beginning.And then,proposed path planning algorithm based on seed points to compute the shortest path between the origin point and the target point to get the initial skeleton.Used minimum spanning tree based on weight as the description module of the skeleton of dendrite spine.In this foundation,the research of detection of spines focused on the change of the vector angle in seed points and the vertices distance of a spine.Experiment shows that the proposed approach can effectively extract the skeleton of the dendrite and achieve a better result on spines detection.

关 键 词：树突棘 种子点 区域分割 骨架提取 突棘检测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]