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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >A STRATEGY FOR IDENTIFYING FLUORESCENCE INTENSITY PROFILES OF SINGLE ROD-SHAPED CELLS
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A STRATEGY FOR IDENTIFYING FLUORESCENCE INTENSITY PROFILES OF SINGLE ROD-SHAPED CELLS

机译:识别单杆状细胞荧光强度分布的策略

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摘要

The extraction of fluorescence intensity profiles of single cells from image data is a common challenge in cell biology. The manual segmentation of cells, the extraction of cell orientation and finally the extraction of intensity profiles are time-consuming tasks. This article proposes a routine for the segmentation of single rod-shaped cells (i.e. without neighboring cells in a distance of the cell length) from image data combined with an extraction of intensity distributions along the longitudinal cell axis under the aggravated conditions of (i) a low spatial resolution and (ii) lacking information on the imaging system i.e. the point spread function and signal-to-noise ratio. The algorithm named cipsa transfers a new approach from particle streak velocimetry to cell classification interpreting the rod-shaped as streak-like structures. An automatic reduction of systematic errors such as photobleaching and defocusing is included to guarantee robustness of the proposed approach under the described conditions and to the convenience of end-users unfamiliar with image processing. Performance of the algorithm has been tested on image sequences with high noise level produced by an overlay of different error sources. The developed algorithm provides a user-friendly, stand-alone procedure.
机译:从图像数据中提取单个细胞的荧光强度分布图是细胞生物学中的一个普遍挑战。手动分割细胞,提取细胞方向以及最后提取强度分布图是耗时的任务。本文提出了一种用于从图像数据中分割单个棒状细胞(即,在细胞长度的距离内没有相邻细胞)的程序,并结合了在(i)加剧条件下沿细胞纵向轴的强度分布的提取空间分辨率低,并且(ii)缺乏有关成像系统的信息,即点扩展函数和信噪比。名为cipsa的算法将一种新的方法从粒子条纹测速法转移到细胞分类中,从而将棒状解释为条纹状结构。可以自动减少系统误差,例如光漂白和散焦,以确保所提出的方法在所述条件下具有鲁棒性,并为不熟悉图像处理的最终用户提供便利。该算法的性能已经在由不同误差源的叠加所产生的具有高噪声水平的图像序列上进行了测试。开发的算法提供了一种用户友好的独立过程。

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