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Hybrid Image Processing Technique for the Robust Identification of Unstained Cells in Bright-Field Microscope Images

机译:用于明亮场显微镜图像中未染色细胞的鲁棒识别的混合图像处理技术

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The initial results of a robust technique for the identification of unstained cells in bright-field microscope images captured with high magnification lenses are presented. This is part of an extensive study on the effects of DNA damage to cell viability induced by multi-photon absorption. The method makes use of a variety of image processing algorithms together with expert knowledge of cell morphology during the cell cycle. Single stem cells are identified by first detecting their cell nucleoli and then clustering into nuclear groups. Experimental results, for a representative sample of images, are compared with ground truth labeling by skilled biologists. Despite the low contrast and high variability in appearance of cells in bright-field microscope images, the reported technique displays a detection rate of over 79% for the correct number of identified cells. The methodology implemented has sufficient accuracy and speed for the development of high-throughput robotic systems.
机译:提出了一种稳定技术,用于识别用高放大镜镜片捕获的明场显微镜图像中未染色的细胞的稳定技术。这是对多光子吸收诱导的DNA损伤对细胞活力的影响的广泛研究的一部分。该方法利用各种图像处理算法以及细胞周期中细胞形态的专家知识。通过首先检测其细胞核液然后聚集到核基团中来鉴定单干细胞。将实验结果与专业生物学家的代表性样本相比,与地面真理标记进行比较。尽管在亮场显微镜图像中的细胞外观上具有低对比度和高可变性,但报告的技术显示出正确数量的识别细胞的检出量超过79%。实施方法具有足够的准确性和速度来开发高吞吐量机器人系统。

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