Image Quality Ranking Method for Microscopy.
Image Quality Ranking Method for Microscopy.
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DOI：
10.1038/srep28962
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发表时间：
2016-07-01
影响因子：
4.6
通讯作者：
Hänninen PE
中科院分区：
文献类型：
--
作者：
Koho S;Fazeli E;Eriksson JE;Hänninen PE
自动化分析显微镜图像是必要的高分辨率的后续事件的时间增加的需要。手动找到正确的图像进行分析，或从数据分析中删除是当今显微镜研究中常见的日常问题，并且图像数据集的不断增长的大小无助于解决问题。我们提出了一种简单的方法和软件工具，用于根据图像的相对质量对数据集中的图像进行排序。我们证明了我们的方法在STED显微镜样品制备优化图像数据集中找到高质量图像的适用性。通过与主观意见评分以及五种最先进的盲图像质量评估方法的比较，验证了结果。我们还展示了我们的方法如何可以应用于消除无用的失焦图像在高内容筛选实验。我们进一步评估了我们的图像质量排名方法检测失焦图像的能力，通过广泛的模拟，并将其性能与以前发表的，成熟的显微镜自动对焦指标进行比较。
Automated analysis of microscope images is necessitated by the increased need for high-resolution follow up of events in time. Manually finding the right images to be analyzed, or eliminated from data analysis are common day-to-day problems in microscopy research today, and the constantly growing size of image datasets does not help the matter. We propose a simple method and a software tool for sorting images within a dataset, according to their relative quality. We demonstrate the applicability of our method in finding good quality images in a STED microscope sample preparation optimization image dataset. The results are validated by comparisons to subjective opinion scores, as well as five state-of-the-art blind image quality assessment methods. We also show how our method can be applied to eliminate useless out-of-focus images in a High-Content-Screening experiment. We further evaluate the ability of our image quality ranking method to detect out-of-focus images, by extensive simulations, and by comparing its performance against previously published, well-established microscopy autofocus metrics.