Performance of optical flow techniques for motion analysis of fluorescent point signals in confocal microscopy
Performance of optical flow techniques for motion analysis of fluorescent point signals in confocal microscopy
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DOI：
10.1007/s00138-011-0362-8
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发表时间：
2012-07-01
影响因子：
3.3
通讯作者：
Haertel, Steffen
中科院分区：
文献类型：
--
作者：
Delpiano, Jose;Jara, Jorge;Haertel, Steffen
光流法计算矢量场，矢量场确定时变图像序列中物体的表观速度。它们已经在计算机科学中使用自然和合成视频序列进行了广泛的分析。在生命科学中，越来越需要从时间图像序列中提取动力学信息，以揭示微观生物结构的形式和功能之间的相互作用。在这项工作中，我们测试了不同的变分光流技术来量化二维荧光图像序列中生物对象的位移。矢量场的准确性被测试为模拟神经元树突中的蛋白质交通的合成图像序列中的荧光点源的定义位移，以及海马神经元树突中的GABA(B)R1受体亚单位。结果表明，在最大位移为160 nm时，光流场对荧光点光源运动的预测误差在3%以内。当最大位移为640 nm时，凝聚的GABA(B)R1受体亚基的位移可以被正确预测。在这些结果的基础上，我们引入了一个准则来推导出计算实验图像中光流场的最佳参数组合。根据这些结果，可以得到用于图像采集的时间采样频率，以保证对生物对象进行正确的运动估计。
Optical flow approaches calculate vector fields which determine the apparent velocities of objects in time-varying image sequences. They have been analyzed extensively in computer science using both natural and synthetic video sequences. In life sciences, there is an increasing need to extract kinetic information from temporal image sequences which reveals the interplay between form and function of microscopic biological structures. In this work, we test different variational optical flow techniques to quantify the displacements of biological objects in 2D fluorescent image sequences. The accuracy of the vector fields is tested for defined displacements of fluorescent point sources in synthetic image series which mimic protein traffic in neuronal dendrites, and for GABA(B)R1 receptor subunits in dendrites of hippocampal neurons. Our results reveal that optical flow fields predict the movement of fluorescent point sources within an error of 3% for a maximum displacement of 160 nm. Displacement of agglomerated GABA(B)R1 receptor subunits can be predicted correctly for maximum displacements of 640 nm. Based on these results, we introduce a criteria to derive the optimum parameter combinations for the calculation of the optical flow fields in experimental images. From these results, temporal sampling frequencies for image acquisition can be derived to guarantee correct motion estimation for biological objects.