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Knowledge-Based Morphology Quantification of STED Dendritic Spine Images

机译:基于知识的形态学定量STED树突脊柱图像

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Automated quantification of dendritic spine morphology plays an important role in neurobiological research. We present in this paper a novel approach that combines prior knowledge and morphological operators to separate, reconstruct and finally quantify key attributes of stimulated emission depletion microscopy dendritic spine images. The proposed image quantification process is fully automated. Experiment results show its efficiency in handling difficult aspects of neuroimaging analysis.
机译:树枝状脊柱形态的自动化量化在神经生物学研究中起着重要作用。我们本文以本文展示了一种新的方法,将先验知识和形态学算子结合在一起,分离,重建和最终定量刺激排放耗尽显微镜树突状脊柱图像的关键属性。所提出的图像量化过程是完全自动化的。实验结果表明了处理神经影像分析难度方面的效率。

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