Computer Science Department, University of Houston, Houston, TX 77004, USA.
IEEE Trans Med Imaging. 2011 Mar;30(3):632-41. doi: 10.1109/TMI.2010.2090354. Epub 2010 Nov 1.
Dendritic spines form postsynaptic contact sites in the central nervous system. The rapid and spontaneous morphology changes of spines have been widely observed by neurobiologists. Determining the relationship between dendritic spine morphology change and its functional properties such as memory learning is a fundamental yet challenging problem in neurobiology research. In this paper, we propose a novel algorithm to track the morphology change of multiple spines simultaneously in time-lapse neuronal images based on nonrigid registration and integer programming. We also propose a robust scheme to link disappearing-and-reappearing spines. Performance comparisons with other state-of-the-art cell and spine tracking algorithms, and the ground truth show that our approach is more accurate and robust, and it is capable of tracking a large number of neuronal spines in time-lapse confocal microscopy images.
树突棘形成中枢神经系统中的突触后接触位点。神经生物学家广泛观察到棘突的快速和自发形态变化。确定树突棘形态变化与其功能特性（如记忆学习）之间的关系是神经生物学研究中的一个基本但具有挑战性的问题。在本文中，我们提出了一种新的算法，基于非刚性配准和整数规划，在延时神经元图像中同时跟踪多个棘突的形态变化。我们还提出了一种稳健的方案来连接消失和重现的棘突。与其他最先进的细胞和棘突跟踪算法以及真实数据的性能比较表明，我们的方法更准确、更稳健，能够在延时共聚焦显微镜图像中跟踪大量神经元棘突。
