A NOVEL SURFACE-BASED GEOMETRIC APPROACH FOR 3D DENDRITIC SPINE DETECTION FROM MULTI-PHOTON EXCITATION MICROSCOPY IMAGES.
A NOVEL SURFACE-BASED GEOMETRIC APPROACH FOR 3D DENDRITIC SPINE DETECTION FROM MULTI-PHOTON EXCITATION MICROSCOPY IMAGES.
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一种基于多光子激发显微图像进行 3D 树突棘检测的新颖的基于表面的几何方法。
DOI：
10.1109/isbi.2009.5193290
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Wong,StephenTC
中科院分区：
文献类型：
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作者：
Li,Qing;Zhou,Xiaobo;Deng,Zhigang;Baron,Matthew;Teylan,MerileeA;Kim,Yong;Wong,StephenTC
确定树突棘形态与其功能特性之间的关系是神经生物学研究中的一个基本而具有挑战性的问题。特别是，如何准确和自动地分析有意义的结构信息从一个大的显微图像数据集是远远没有得到解决。在本文中，我们提出了一种新的方法，自动神经元重建和脊柱检测荧光显微镜图像。在图像处理之后，获得神经元的骨架，并且将神经元表示为3D表面。在分析物体表面几何特征的基础上，提出了一种新的混合分割方法来检测物体表面的脊。除了脊椎的自动检测，我们的算法是能够提取准确的脊椎的三维结构。与现有算法的比较结果表明，该算法具有更高的准确性和鲁棒性，特别是在检测和分离接触脊时。
Determining the relationship between the dendritic spine morphology and its functional properties is a fundamental while challenging problem in neurobiology research. In particular, how to accurately and automatically analyze meaningful structural information from a large microscopy image dataset is far away from being resolved. In this paper, we propose a novel method for the automated neuron reconstruction and spine detection from fluorescence microscopy images. After image processing, backbone of the neuron is obtained and the neuron is represented as a 3D surface. Based on the analysis of geometric features on the surface, spines are detected by a novel hybrid of two segmentation methods. Besides the automated detection of spines, our algorithm is able to extract accurate 3D structures of spines. Comparison results between our approach and the state of the art shows that our algorithm is more accurate and robust, especially for detecting and separating touching spines.