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Root Mean Square Minimum Distance as a Quality Metric for Stochastic Optical Localization Nanoscopy Images

机译:均方根最小距离作为随机光学定位纳米图像的质量度量

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摘要

A localization algorithm in stochastic optical localization nanoscopy plays an important role in obtaining a high-quality image. A universal and objective metric is crucial and necessary to evaluate qualities of nanoscopy images and performances of localization algorithms. In this paper, we propose root mean square minimum distance (RMSMD) as a quality metric for localization nanoscopy images. RMSMD measures an average, local, and mutual fitness between two sets of points. Its properties common to a distance metric as well as unique to itself are presented. The ambiguity, discontinuity, and inappropriateness of the metrics of accuracy, precision, recall, and Jaccard index, which are currently used in the literature, are analyzed. A numerical example demonstrates the advantages of RMSMD over the four existing metrics that fail to distinguish qualities of different nanoscopy images in certain conditions. The unbiased Gaussian estimator that achieves the Fisher information and Cramer-Rao lower bound (CRLB) of a single data frame is proposed to benchmark the quality of localization nanoscopy images and the performance of localization algorithms. The information-achieving estimator is simulated in an example and the result demonstrates the superior sensitivity of RMSMD over the other four metrics. As a universal and objective metric, RMSMD can be broadly employed in various applications to measure the mutual fitness of two sets of points.
机译:随机光学定位纳米技术中的定位算法在获取高质量图像中起着重要作用。通用客观的指标对于评估纳米显微镜图像的质量和定位算法的性能至关重要且必不可少。在本文中,我们提出了均方根最小距离(RMSMD)作为定位纳米图像的质量度量。 RMSMD测量两组点之间的平均,局部和相互适应度。提出了距离度量共有的属性,以及距离度量本身唯一的属性。分析了目前在文献中使用的准确性,准确性,召回率和Jaccard指标的歧义,不连续性和不适当性。数值示例证明了RMSMD相对于现有的四个度量的优势,这些度量在特定条件下无法区分不同纳米显微镜图像的质量。提出了实现单个数据帧的Fisher信息和Cramer-Rao下界(CRLB)的无偏高斯估计量,以对定位纳米显微镜图像的质量和定位算法的性能进行基准测试。在一个示例中对信息获取估计器进行了仿真,结果证明了RMSMD优于其他四个指标。作为一种通用和客观的度量,RMSMD可以广泛用于各种应用中,以测量两组点的相互适应性。

著录项

  • 期刊名称 Scientific Reports
  • 作者

    Yi Sun;

  • 作者单位
  • 年(卷),期 -1(8),-1
  • 年度 -1
  • 页码 17211
  • 总页数 11
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

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