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Recognition of Unstained Live Drosophila Cells in Microscope Images

机译:在显微镜图像中识别未染色的活果蝇细胞

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In order to localise tagged proteins in living cells, the surrounding cells must be recognised first. Based on previous work regarding cell recognition in bright-field images, we propose an approach to the automated recognition of unstained live Drosophila cells, which are of high biological relevance. In order to achieve this goal, the original methods were extended to enable the additional application of an alternative microscopy technique, since the exclusive usage of bright-field images does not allow for an accurate segmentation of the considered cells. In order to cope with the increased number of parameters to be set, a genetic algorithm is applied. Furthermore, the employed segmentation and classification techniques needed to be adapted to the new cell characteristics. Therefore, a modified active contour approach and an enhanced feature set, allowing for a more detailed description of the obtained segments, are introduced.
机译:为了将标记的蛋白质定位在活细胞中,必须首先识别周围的细胞。基于以前关于在亮场图像中的细胞识别的工作,我们提出了一种方法来实现未染色的活果蝇细胞的自动识别,这具有高生物相关性。为了实现这一目标,扩展了原始方法以实现替代显微镜技术的附加应用,因为亮场图像的独占用途不允许考虑的单元的准确分割。为了应对要设置的参数数量增加,应用了一种遗传算法。此外,所采用的分段和分类技术需要适应新的细胞特征。因此,介绍了修改的主动轮廓方法和增强特征集,允许获得所获得的段的更详细描述。

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