Recognition of Unstained Live Drosophila Cells in Microscope Images

M. Tscherepanow, N. Jensen, F. Kummert
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引用次数: 20

Abstract

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.
未染色活果蝇细胞在显微镜下的识别
为了在活细胞中定位标记蛋白,必须首先识别周围的细胞。基于以往关于亮场图像中细胞识别的工作,我们提出了一种具有高度生物学相关性的未染色活果蝇细胞的自动识别方法。为了实现这一目标,原来的方法被扩展,以使另一种显微镜技术的额外应用,因为光场图像的独家使用不允许考虑的细胞的准确分割。为了应对需要设置的参数数量的增加,采用了遗传算法。此外,所采用的分割和分类技术需要适应新的细胞特征。因此,引入了一种改进的主动轮廓方法和增强的特征集,允许对所获得的部分进行更详细的描述。
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