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Cell detection in phase-contrast images used for alpha-particle track-etch dosimetry: a semi-automated approach

机译:用于α粒子轨迹蚀刻剂量法的相衬图像中的细胞检测:一种半自动方法

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摘要

A novel alpha-particle irradiator has recently been developed that provides the ability to characterize cell response. The irradiator is comprised of a collimated, planar alpha-particle source which, from below, irradiates cells cultured on a track-etch material. Cells are imaged using phase-contrast microscopy before and following irradiation to obtain geometric information and survival rates; these can be used with data from alpha-particle track images to assess cell response. A key step in this process is determining cell location within the pre-irradiation images. Although this can be done completely by a human observer, the number of images requiring analysis makes the process time-consuming and tedious. To reduce the potential human error and decrease user interaction time, a semi-automated, computer-aided method of cell detection has been developed. The method employs a two-level adaptive thresholding technique to obtain size and position information about potential cell cytoplasms and nuclei. Proximity and geometry-based thresholds are then used to mark structures as cells. False-positive detections front the automated algorithm are due mostly to imperfections in the track-etch background, camera effects and cellular residue. To correct for these, a human observer reviews all detected structures, discarding false positives. When analysing two randomly selected cell dish image databases, the semi-automated method detected 92-94% of all cells and 94-97% of cells with a well-defined cytoplasm and nucleus while reducing human workload by 32-83%.
机译:最近已经开发了一种新颖的α-粒子辐照器,其提供了表征细胞反应的能力。照射器由准直的平面α粒子源组成,该源从下方照射在轨迹蚀刻材料上培养的细胞。在照射前后,使用相差显微镜对细胞成像,以获得几何信息和存活率;这些可与来自alpha粒子轨迹图像的数据一起使用,以评估细胞反应。此过程中的关键步骤是确定预照射图像内的细胞位置。尽管这可以由观察者完全完成,但是需要分析的图像数量使该过程既费时又繁琐。为了减少潜在的人为错误并减少用户交互时间,已经开发了一种半自动的计算机辅助细胞检测方法。该方法采用两级自适应阈值化技术来获取有关潜在细胞质和细胞核的大小和位置信息。然后使用基于接近度和基于几何的阈值将结构标记为单元。自动化算法之前的假阳性检测主要是由于轨迹蚀刻背景,相机效果和细胞残留物的缺陷所致。为了纠正这些问题,人类观察者检查了所有检测到的结构,并丢弃了假阳性。当分析两个随机选择的细胞培养皿图像数据库时,半自动化方法检测到所有细胞的92-94%和具有明确细胞质和细胞核的细胞的94-97%,同时将人类工作量减少了32-83%。

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