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Unstained viable cell recognition in phase-contrast microscopy

机译:相衬显微镜中未染色的活细胞识别

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Individual cell recognition is a relevant task to be accomplished when single-ion microbeam irradiations are performed. At INFN-LNL facility cell visualization system is based on a phase-contrast optical microscope, without the use of any cell dye. Unstained cells are seeded in the special designed Petri dish, between two mylar foils, and at present the cell recognition is achieved ,anually by an expert operator. Nevertheless, this procedure is time consuming and sometimes it could be not practical if the amount of living cells to be irradiated is large. To reduce the time needed to recognize unstained cells on the Petri dish, it has been designed and implemented an automated, parallel algorithm. Overlapping ROIs sliding in steps over the captured grayscale image are firstly pre-classified and potential cell markers for the segmentation are obtained. Segmented objects are additionally classified to categorize cell bodies from other structures considered as sample dirt or background. As a result, cell coordinates are passed to the dedicated CELLView program that controls all the LNL single-ion microbeam irradiation protocol, including the positioning of individual cells in front of the ion beam. Unstained cell recognition system was successfully tested in experimental conditions with two different mylar surfaces. The recognition time and accuracy was acceptable, however, improvements in speed would be useful.
机译:当执行单离子微束照射时,单个细胞识别是要完成的相关任务。在INFN-LNL设施中,细胞可视化系统基于相衬光学显微镜,无需使用任何细胞染料。将未染色的细胞播种在经过特殊设计的培养皿中,位于两个聚酯薄膜箔之间,目前,由专业操作员每年都可以实现对细胞的识别。然而,该过程很耗时,并且如果要辐照的活细胞数量很大,有时可能不切实际。为了减少识别陪替氏培养皿上未染色细胞所需的时间,已设计并实施了自动并行算法。首先对在捕获的灰度图像上逐步滑动的重叠ROI进行预分类,然后获得用于分割的潜在细胞标记。另外,对分割的对象进行分类,以将来自其他结构的细胞体分类为样本污垢或背景。结果,细胞坐标被传递到专用的CELLView程序,该程序控制所有LNL单离子微束辐照协议,包括将单个细胞放置在离子束前面。未染色的细胞识别系统已在具有两个不同聚酯薄膜表面的实验条件下成功测试。识别时间和准确性是可以接受的,但是,提高速度将很有用。

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